SYMBOL INDEX (732 symbols across 87 files) FILE: examples/video_analysis_per_frame.py function forFrame (line 13) | def forFrame(frame_number, output_array, output_count, returned_frame): FILE: examples/video_analysis_per_second.py function forSecond (line 13) | def forSecond(frame_number, output_arrays, count_arrays, average_count, ... FILE: imageai/Classification/Custom/__init__.py class ClassificationModelTrainer (line 26) | class ClassificationModelTrainer(): method __init__ (line 33) | def __init__(self) -> None: method __set_training_param (line 49) | def __set_training_param(self) -> None: method __set_transfer_learning_mode (line 90) | def __set_transfer_learning_mode(self) -> None: method __load_data (line 114) | def __load_data(self, batch_size : int = 8) -> None: method setDataDirectory (line 136) | def setDataDirectory(self, data_directory : str = "") -> None: method setModelTypeAsMobileNetV2 (line 162) | def setModelTypeAsMobileNetV2(self) -> None: method setModelTypeAsResNet50 (line 170) | def setModelTypeAsResNet50(self) -> None: method setModelTypeAsInceptionV3 (line 178) | def setModelTypeAsInceptionV3(self) -> None: method setModelTypeAsDenseNet121 (line 186) | def setModelTypeAsDenseNet121(self) -> None: method freezeAllLayers (line 194) | def freezeAllLayers(self) -> None: method fineTuneAllLayers (line 202) | def fineTuneAllLayers(self) -> None: method trainModel (line 208) | def trainModel( class CustomImageClassification (line 333) | class CustomImageClassification: method __init__ (line 357) | def __init__(self) -> None: method __load_image (line 366) | def __load_image(self, image_input: Union[str, np.ndarray, Image.Image... method __load_classes (line 391) | def __load_classes(self): method setModelPath (line 398) | def setModelPath(self, path : str) -> None: method setJsonPath (line 411) | def setJsonPath(self, path : str) -> None: method setModelTypeAsMobileNetV2 (line 422) | def setModelTypeAsMobileNetV2(self) -> None: method setModelTypeAsResNet50 (line 429) | def setModelTypeAsResNet50(self) -> None: method setModelTypeAsInceptionV3 (line 436) | def setModelTypeAsInceptionV3(self) -> None: method setModelTypeAsDenseNet121 (line 443) | def setModelTypeAsDenseNet121(self) -> None: method useCPU (line 450) | def useCPU(self): method loadModel (line 460) | def loadModel(self) -> None: method classifyImage (line 516) | def classifyImage(self, image_input: Union[str, np.ndarray, Image.Imag... FILE: imageai/Classification/Custom/training_params.py function resnet50_train_params (line 8) | def resnet50_train_params(): function inception_v3_train_params (line 19) | def inception_v3_train_params(): function mobilenet_v2_train_params (line 31) | def mobilenet_v2_train_params(): function densenet121_train_params (line 43) | def densenet121_train_params(): FILE: imageai/Classification/__init__.py class ImageClassification (line 28) | class ImageClassification: method __init__ (line 48) | def __init__(self) -> None: method setModelPath (line 57) | def setModelPath(self, path: str): method __load_classes (line 72) | def __load_classes(self) -> List[str]: method __load_image (line 76) | def __load_image(self, image_input: Union[str, np.ndarray, Image.Image... method setModelTypeAsResNet50 (line 101) | def setModelTypeAsResNet50(self): method setModelTypeAsDenseNet121 (line 109) | def setModelTypeAsDenseNet121(self): method setModelTypeAsInceptionV3 (line 117) | def setModelTypeAsInceptionV3(self): method setModelTypeAsMobileNetV2 (line 125) | def setModelTypeAsMobileNetV2(self): method useCPU (line 133) | def useCPU(self): method loadModel (line 143) | def loadModel(self): method classifyImage (line 191) | def classifyImage(self, image_input: Union[str, np.ndarray, Image.Imag... FILE: imageai/Detection/Custom/__init__.py class DetectionModelTrainer (line 29) | class DetectionModelTrainer: method __init__ (line 35) | def __init__(self) -> None: method __set_training_param (line 59) | def __set_training_param(self, epochs : int, accumulate : int) -> None: method __load_model (line 108) | def __load_model(self) -> None: method __load_data (line 124) | def __load_data(self) -> None: method setModelTypeAsYOLOv3 (line 139) | def setModelTypeAsYOLOv3(self) -> None: method setModelTypeAsTinyYOLOv3 (line 146) | def setModelTypeAsTinyYOLOv3(self) -> None: method setDataDirectory (line 153) | def setDataDirectory(self, data_directory: str): method setTrainConfig (line 185) | def setTrainConfig(self, object_names_array: List[str], batch_size: in... method trainModel (line 207) | def trainModel(self) -> None: class CustomObjectDetection (line 322) | class CustomObjectDetection: method __init__ (line 328) | def __init__(self) -> None: method setModelTypeAsYOLOv3 (line 340) | def setModelTypeAsYOLOv3(self) -> None: method setModelTypeAsTinyYOLOv3 (line 347) | def setModelTypeAsTinyYOLOv3(self) -> None: method setModelPath (line 354) | def setModelPath(self, model_path: str): method setJsonPath (line 365) | def setJsonPath(self, configuration_json: str): method __load_classes_and_anchors (line 368) | def __load_classes_and_anchors(self) -> List[str]: method __load_image_yolo (line 375) | def __load_image_yolo(self, input_image : Union[str, np.ndarray, Image... method useCPU (line 422) | def useCPU(self): method loadModel (line 433) | def loadModel(self) -> None: method detectObjectsFromImage (line 465) | def detectObjectsFromImage(self, class CustomVideoObjectDetection (line 646) | class CustomVideoObjectDetection: method __init__ (line 660) | def __init__(self): method setModelTypeAsYOLOv3 (line 663) | def setModelTypeAsYOLOv3(self): method setModelTypeAsTinyYOLOv3 (line 666) | def setModelTypeAsTinyYOLOv3(self): method setModelPath (line 669) | def setModelPath(self, model_path: str): method setJsonPath (line 673) | def setJsonPath(self, configuration_json: str): method loadModel (line 676) | def loadModel(self): method useCPU (line 679) | def useCPU(self): method detectObjectsFromVideo (line 682) | def detectObjectsFromVideo(self, input_file_path="", camera_input=None... FILE: imageai/Detection/Custom/yolo/compute_loss.py function bbox_iou (line 8) | def bbox_iou(box1, box2, x1y1x2y2=True, GIoU=False, DIoU=False, CIoU=Fal... function compute_loss (line 55) | def compute_loss(loss_layers, targets, device="cpu"): function build_targets (line 129) | def build_targets(p, targets, loss_layers, device="cpu"): FILE: imageai/Detection/Custom/yolo/custom_anchors.py function generate_anchors (line 9) | def generate_anchors(dataset, n=9, img_size=416, thr=4.0, gen=1000, verb... FILE: imageai/Detection/Custom/yolo/dataset.py class LoadImagesAndLabels (line 13) | class LoadImagesAndLabels(Dataset): method __init__ (line 15) | def __init__(self, path : str, net_dim=(416, 416), train=True): method __len__ (line 42) | def __len__(self) -> int: method __img_path2label_path (line 45) | def __img_path2label_path(self, path : str) -> str: method __getitem__ (line 49) | def __getitem__(self, idx) -> Tuple[torch.Tensor, torch.Tensor]: method __xywhn2xyxy (line 57) | def __xywhn2xyxy(self, nlabel : torch.Tensor, width : int, height : in... method __load_data (line 70) | def __load_data(self, img_path : str, label : np.ndarray) -> Tuple[tor... method __load_raw_label (line 77) | def __load_raw_label(self, label_path : str): method __process_label (line 87) | def __process_label(self, label : np.ndarray, image_width : int, image... method collate_fn (line 121) | def collate_fn(self, batch) -> Tuple[torch.Tensor, torch.Tensor]: FILE: imageai/Detection/Custom/yolo/metric.py function ap_per_class (line 9) | def ap_per_class(tp, conf, pred_cls, target_cls): function compute_ap (line 63) | def compute_ap(recall, precision): FILE: imageai/Detection/Custom/yolo/validate.py function xywh2xyxy (line 14) | def xywh2xyxy(box_coord : torch.Tensor): function process_batch (line 27) | def process_batch(detections, labels, iouv): function run (line 53) | def run(model, val_dataloader, num_class, net_dim=416, nms_thresh=0.6, o... FILE: imageai/Detection/__init__.py class ImageReadMode (line 25) | class ImageReadMode(Enum): class ObjectDetection (line 42) | class ObjectDetection: method __init__ (line 61) | def __init__(self) -> None: method __load_classes (line 75) | def __load_classes(self, path: str) -> List[str]: method __load_image_yolo (line 80) | def __load_image_yolo(self, input_image : Union[str, np.ndarray, Image... method __save_temp_img (line 122) | def __save_temp_img(self, input_image : Union[np.ndarray, Image.Image]... method __load_image_retinanet (line 139) | def __load_image_retinanet(self, input_image : str) -> Tuple[List[str]... method setModelTypeAsYOLOv3 (line 174) | def setModelTypeAsYOLOv3(self): method setModelTypeAsTinyYOLOv3 (line 182) | def setModelTypeAsTinyYOLOv3(self): method setModelTypeAsRetinaNet (line 190) | def setModelTypeAsRetinaNet(self): method setModelPath (line 198) | def setModelPath(self, path: str) -> None: method useCPU (line 214) | def useCPU(self): method loadModel (line 225) | def loadModel(self) -> None: method CustomObjects (line 263) | def CustomObjects(self, **kwargs): method detectObjectsFromImage (line 294) | def detectObjectsFromImage(self, class VideoObjectDetection (line 541) | class VideoObjectDetection: method __init__ (line 556) | def __init__(self): method setModelTypeAsYOLOv3 (line 559) | def setModelTypeAsYOLOv3(self): method setModelTypeAsTinyYOLOv3 (line 562) | def setModelTypeAsTinyYOLOv3(self): method setModelTypeAsRetinaNet (line 565) | def setModelTypeAsRetinaNet(self): method setModelPath (line 568) | def setModelPath(self, model_path: str): method loadModel (line 572) | def loadModel(self): method useCPU (line 575) | def useCPU(self): method CustomObjects (line 578) | def CustomObjects(self, **kwargs): method detectObjectsFromVideo (line 581) | def detectObjectsFromVideo(self, input_file_path="", camera_input=None... FILE: imageai/backend_check/model_extension.py function extension_check (line 3) | def extension_check(file_path: str): FILE: imageai/densenet121/__init__.py class DenseNet121Pretrained (line 12) | class DenseNet121Pretrained: method __init__ (line 17) | def __init__(self, label_path : str) -> None: method __load_classes (line 24) | def __load_classes(self, path : str) -> List[str]: method __load_image (line 29) | def __load_image(self, image_path : str) -> Tuple[List[str], torch.Ten... method set_model_path (line 72) | def set_model_path(self, path : str) -> None: method load_model (line 84) | def load_model(self) -> None: method classify (line 111) | def classify(self, image_path : str, top_n : int = 5, verbose : bool =... FILE: imageai/inceptionv3/__init__.py class InceptionV3Pretrained (line 12) | class InceptionV3Pretrained: method __init__ (line 17) | def __init__(self, label_path : str) -> None: method __load_classes (line 24) | def __load_classes(self, path : str) -> List[str]: method __load_image (line 29) | def __load_image(self, image_path : str) -> Tuple[List[str], torch.Ten... method set_model_path (line 72) | def set_model_path(self, path : str) -> None: method load_model (line 84) | def load_model(self) -> None: method classify (line 99) | def classify(self, image_path : str, top_n : int = 5, verbose : bool =... FILE: imageai/mobilenetv2/__init__.py class MobileNetV2Pretrained (line 12) | class MobileNetV2Pretrained: method __init__ (line 17) | def __init__(self, label_path : str) -> None: method __load_classes (line 24) | def __load_classes(self, path : str) -> List[str]: method __load_image (line 29) | def __load_image(self, image_path : str) -> Tuple[List[str], torch.Ten... method set_model_path (line 72) | def set_model_path(self, path : str) -> None: method load_model (line 84) | def load_model(self) -> None: method classify (line 99) | def classify(self, image_path : str, top_n : int = 5, verbose : bool =... FILE: imageai/resnet50/__init__.py class ResNet50Pretrained (line 11) | class ResNet50Pretrained: method __init__ (line 16) | def __init__(self, label_path : str) -> None: method __load_classes (line 23) | def __load_classes(self, path : str) -> List[str]: method __load_image (line 28) | def __load_image(self, image_path : str) -> Tuple[List[str], torch.Ten... method set_model_path (line 71) | def set_model_path(self, path : str) -> None: method load_model (line 83) | def load_model(self) -> None: method classify (line 98) | def classify(self, image_path : str, top_n : int = 5, verbose : bool =... FILE: imageai/retinanet/utils.py function read_file (line 11) | def read_file(path: str) -> torch.Tensor: function decode_image (line 25) | def decode_image(input: torch.Tensor, mode: ImageReadMode = ImageReadMod... function read_image (line 47) | def read_image(path: str, mode: ImageReadMode = ImageReadMode.UNCHANGED)... function _generate_color_palette (line 67) | def _generate_color_palette(num_objects: int): function make_grid (line 72) | def make_grid( function draw_bounding_boxes_and_labels (line 180) | def draw_bounding_boxes_and_labels( function tensor_to_ndarray (line 269) | def tensor_to_ndarray( FILE: imageai/yolov3/tiny_yolov3.py class YoloV3Tiny (line 10) | class YoloV3Tiny(nn.Module): method __init__ (line 12) | def __init__( method get_loss_layers (line 64) | def get_loss_layers(self) -> List[torch.Tensor]: method __route_layer (line 67) | def __route_layer(self, y1 : torch.Tensor, y2 : Optional[torch.Tensor]... method forward (line 72) | def forward(self, x : torch.Tensor) -> torch.Tensor: FILE: imageai/yolov3/utils.py function draw_bbox_and_label (line 10) | def draw_bbox_and_label(x : torch.Tensor, label : str, img : np.ndarray)... function letterbox_image (line 23) | def letterbox_image( function prepare_image (line 46) | def prepare_image( function bbox_iou (line 57) | def bbox_iou(bbox1 : torch.Tensor, bbox2 : torch.Tensor, device="cpu"): function transform_prediction (line 77) | def transform_prediction( function get_predictions (line 160) | def get_predictions( FILE: imageai/yolov3/yolov3.py function noop (line 10) | def noop(x): class DetectionLayer (line 13) | class DetectionLayer(nn.Module): method __init__ (line 15) | def __init__( method __get_anchors (line 41) | def __get_anchors( method forward (line 48) | def forward(self, x : torch.Tensor): class ConvLayer (line 75) | class ConvLayer(nn.Module): method __init__ (line 77) | def __init__(self, in_f : int, out_f : int, kernel_size : int = 3, method forward (line 89) | def forward(self, x : torch.Tensor): class YoloV3 (line 92) | class YoloV3(nn.Module): method __init__ (line 94) | def __init__( method get_loss_layers (line 243) | def get_loss_layers(self) -> List[torch.Tensor]: method __route_layer (line 246) | def __route_layer(self, y1 : torch.Tensor, y2 : Optional[torch.Tensor]... method __shortcut_layer (line 251) | def __shortcut_layer(self, method forward (line 258) | def forward(self, x : torch.Tensor) -> torch.Tensor: FILE: imageai_tf_deprecated/Classification/Custom/__init__.py class ClassificationModelTrainer (line 10) | class ClassificationModelTrainer: method __init__ (line 17) | def __init__(self): method setModelTypeAsSqueezeNet (line 31) | def setModelTypeAsSqueezeNet(self): method setModelTypeAsMobileNetV2 (line 34) | def setModelTypeAsMobileNetV2(self): method setModelTypeAsResNet (line 43) | def setModelTypeAsResNet(self): method setModelTypeAsResNet50 (line 46) | def setModelTypeAsResNet50(self): method setModelTypeAsDenseNet (line 56) | def setModelTypeAsDenseNet(self): method setModelTypeAsDenseNet121 (line 59) | def setModelTypeAsDenseNet121(self): method setModelTypeAsInceptionV3 (line 67) | def setModelTypeAsInceptionV3(self): method setDataDirectory (line 75) | def setDataDirectory(self, data_directory="", train_subdirectory="trai... method lr_schedule (line 119) | def lr_schedule(self, epoch): method trainModel (line 147) | def trainModel(self, num_objects, num_experiments=200, enhance_data=Fa... class CustomImageClassification (line 401) | class CustomImageClassification: method __init__ (line 417) | def __init__(self): method setModelPath (line 427) | def setModelPath(self, model_path): method setJsonPath (line 437) | def setJsonPath(self, model_json): method setModelTypeAsMobileNetV2 (line 446) | def setModelTypeAsMobileNetV2(self): method setModelTypeAsResNet50 (line 454) | def setModelTypeAsResNet50(self): method setModelTypeAsDenseNet121 (line 462) | def setModelTypeAsDenseNet121(self): method setModelTypeAsInceptionV3 (line 470) | def setModelTypeAsInceptionV3(self): method loadModel (line 478) | def loadModel(self, classification_speed="normal", num_objects=10): method loadFullModel (line 541) | def loadFullModel(self, classification_speed="normal", num_objects=10): method getModels (line 572) | def getModels(self): method classifyImage (line 580) | def classifyImage(self, image_input, result_count=5, input_type="file"): method predictImage (line 664) | def predictImage(self, image_input, result_count=5, input_type="file"): FILE: imageai_tf_deprecated/Classification/__init__.py class ImageClassification (line 7) | class ImageClassification: method __init__ (line 22) | def __init__(self): method setModelPath (line 29) | def setModelPath(self, model_path): method setModelTypeAsSqueezeNet (line 39) | def setModelTypeAsSqueezeNet(self): method setModelTypeAsMobileNetV2 (line 42) | def setModelTypeAsMobileNetV2(self): method setModelTypeAsResNet (line 51) | def setModelTypeAsResNet(self): method setModelTypeAsResNet50 (line 54) | def setModelTypeAsResNet50(self): method setModelTypeAsDenseNet (line 63) | def setModelTypeAsDenseNet(self): method setModelTypeAsDenseNet121 (line 66) | def setModelTypeAsDenseNet121(self): method setModelTypeAsInceptionV3 (line 74) | def setModelTypeAsInceptionV3(self): method loadModel (line 82) | def loadModel(self, classification_speed="normal"): method classifyImage (line 146) | def classifyImage(self, image_input, result_count=5, input_type="file"): method predictImage (line 231) | def predictImage(self, image_input, result_count=5, input_type="file"): FILE: imageai_tf_deprecated/Detection/Custom/__init__.py class DetectionModelTrainer (line 25) | class DetectionModelTrainer: method __init__ (line 32) | def __init__(self): method setModelTypeAsYOLOv3 (line 70) | def setModelTypeAsYOLOv3(self): method setDataDirectory (line 78) | def setDataDirectory(self, data_directory): method setGpuUsage (line 134) | def setGpuUsage(self, train_gpus): method setTrainConfig (line 152) | def setTrainConfig(self, object_names_array, batch_size=4, num_experi... method trainModel (line 198) | def trainModel(self): method evaluateModel (line 320) | def evaluateModel(self, model_path, json_path, batch_size=4, iou_thres... method _create_training_instances (line 456) | def _create_training_instances(self, method _create_callbacks (line 511) | def _create_callbacks(self, saved_weights_name, model_to_save): method _create_model (line 537) | def _create_model( class CustomObjectDetection (line 607) | class CustomObjectDetection: method __init__ (line 613) | def __init__(self): method setModelTypeAsYOLOv3 (line 625) | def setModelTypeAsYOLOv3(self): method setModelPath (line 632) | def setModelPath(self, detection_model_path): method setJsonPath (line 641) | def setJsonPath(self, configuration_json): method loadModel (line 649) | def loadModel(self): method detectObjectsFromImage (line 668) | def detectObjectsFromImage(self, input_image="", output_image_path="",... class CustomVideoObjectDetection (line 861) | class CustomVideoObjectDetection: method __init__ (line 870) | def __init__(self): method setModelTypeAsYOLOv3 (line 883) | def setModelTypeAsYOLOv3(self): method setModelPath (line 893) | def setModelPath(self, detection_model_path): method setJsonPath (line 903) | def setJsonPath(self, configuration_json): method loadModel (line 912) | def loadModel(self): method detectObjectsFromVideo (line 931) | def detectObjectsFromVideo(self, input_file_path="", camera_input=None... class BoundBox (line 1211) | class BoundBox: method __init__ (line 1212) | def __init__(self, xmin, ymin, xmax, ymax, objness=None, classes=None): method get_label (line 1222) | def get_label(self): method get_score (line 1228) | def get_score(self): class CustomDetectionUtils (line 1235) | class CustomDetectionUtils: method __init__ (line 1236) | def __init__(self, labels): method _sigmoid (line 1247) | def _sigmoid(x): method decode_netout (line 1250) | def decode_netout(self, netout, anchors, obj_thresh, net_h, net_w): method correct_yolo_boxes (line 1284) | def correct_yolo_boxes(boxes, image_h, image_w, net_h, net_w): method _interval_overlap (line 1294) | def _interval_overlap(self, interval_a, interval_b): method bbox_iou (line 1308) | def bbox_iou(self, box1, box2): method do_nms (line 1322) | def do_nms(self, boxes, nms_thresh): method get_boxes (line 1342) | def get_boxes(self, boxes, labels, thresh): method label_color (line 1356) | def label_color(self, label): method draw_boxes_and_caption (line 1372) | def draw_boxes_and_caption(self, image_frame, v_boxes, v_labels, v_sco... FILE: imageai_tf_deprecated/Detection/Custom/callbacks.py class CustomTensorBoard (line 6) | class CustomTensorBoard(TensorBoard): method __init__ (line 9) | def __init__(self, log_every=1, **kwargs): method on_batch_end (line 14) | def on_batch_end(self, batch, logs=None): class CustomModelCheckpoint (line 29) | class CustomModelCheckpoint(ModelCheckpoint): method __init__ (line 32) | def __init__(self, model_to_save, **kwargs): method on_epoch_end (line 36) | def on_epoch_end(self, epoch, logs=None): FILE: imageai_tf_deprecated/Detection/Custom/evaluate.py function _main_ (line 12) | def _main_(args): FILE: imageai_tf_deprecated/Detection/Custom/gen_anchors.py function IOU (line 7) | def IOU(ann, centroids): function avg_IOU (line 27) | def avg_IOU(anns, centroids): function run_kmeans (line 37) | def run_kmeans(ann_dims, anchor_num): function generateAnchors (line 73) | def generateAnchors(train_annotation_folder, train_image_folder, train_c... FILE: imageai_tf_deprecated/Detection/Custom/generator.py class BatchGenerator (line 8) | class BatchGenerator(Sequence): method __init__ (line 9) | def __init__(self, method __len__ (line 38) | def __len__(self): method __getitem__ (line 41) | def __getitem__(self, idx): method _get_net_size (line 150) | def _get_net_size(self, idx): method _aug_image (line 158) | def _aug_image(self, instance, net_h, net_w): method on_epoch_end (line 201) | def on_epoch_end(self): method num_classes (line 205) | def num_classes(self): method size (line 208) | def size(self): method get_anchors (line 211) | def get_anchors(self): method load_annotation (line 219) | def load_annotation(self, i): method load_image (line 231) | def load_image(self, i): FILE: imageai_tf_deprecated/Detection/Custom/utils/bbox.py class BoundBox (line 6) | class BoundBox: method __init__ (line 7) | def __init__(self, xmin, ymin, xmax, ymax, c = None, classes = None): method get_label (line 19) | def get_label(self): method get_score (line 25) | def get_score(self): function _interval_overlap (line 31) | def _interval_overlap(interval_a, interval_b): function bbox_iou (line 46) | def bbox_iou(box1, box2): function draw_boxes (line 62) | def draw_boxes(image, boxes, labels, obj_thresh, quiet=True): FILE: imageai_tf_deprecated/Detection/Custom/utils/colors.py function get_color (line 1) | def get_color(label): FILE: imageai_tf_deprecated/Detection/Custom/utils/image.py function _rand_scale (line 6) | def _rand_scale(scale): function _constrain (line 11) | def _constrain(min_v, max_v, value): function random_flip (line 22) | def random_flip(image, flip): function correct_bounding_boxes (line 28) | def correct_bounding_boxes(boxes, new_w, new_h, net_w, net_h, dx, dy, fl... function random_distort_image (line 58) | def random_distort_image(image, hue=18, saturation=1.5, exposure=1.5): function apply_random_scale_and_crop (line 80) | def apply_random_scale_and_crop(image, new_w, new_h, net_w, net_h, dx, dy): FILE: imageai_tf_deprecated/Detection/Custom/utils/multi_gpu_model.py function multi_gpu_model (line 6) | def multi_gpu_model(model, gpus): FILE: imageai_tf_deprecated/Detection/Custom/utils/utils.py function _sigmoid (line 8) | def _sigmoid(x): function makedirs (line 12) | def makedirs(path): function evaluate (line 20) | def evaluate(model, function correct_yolo_boxes (line 136) | def correct_yolo_boxes(boxes, image_h, image_w, net_h, net_w): function do_nms (line 154) | def do_nms(boxes, nms_thresh): function decode_netout (line 175) | def decode_netout(netout, anchors, obj_thresh, net_h, net_w): function preprocess_input (line 217) | def preprocess_input(image, net_h, net_w): function normalize (line 239) | def normalize(image): function get_yolo_boxes (line 243) | def get_yolo_boxes(model, images, net_h, net_w, anchors, obj_thresh, nms... function compute_overlap (line 276) | def compute_overlap(a, b): function compute_ap (line 304) | def compute_ap(recall, precision): function _softmax (line 332) | def _softmax(x, axis=-1): FILE: imageai_tf_deprecated/Detection/Custom/voc.py function parse_voc_annotation (line 6) | def parse_voc_annotation(ann_dir, img_dir, cache_name, labels=[]): FILE: imageai_tf_deprecated/Detection/YOLO/utils.py function yolo_head (line 8) | def yolo_head(feats, anchors, num_classes, input_shape, calc_loss=False): function yolo_correct_boxes (line 36) | def yolo_correct_boxes(box_xy, box_wh, input_shape, image_shape): function yolo_boxes_and_scores (line 62) | def yolo_boxes_and_scores(feats, anchors, num_classes, input_shape, imag... function yolo_eval (line 73) | def yolo_eval(yolo_outputs, function letterbox_image (line 118) | def letterbox_image(image, size): function correct_yolo_boxes (line 133) | def correct_yolo_boxes(boxes, image_h, image_w, net_h, net_w): class BoundBox (line 152) | class BoundBox: method __init__ (line 153) | def __init__(self, xmin, ymin, xmax, ymax, objness = None, classes = N... method get_label (line 165) | def get_label(self): method get_score (line 171) | def get_score(self): function _interval_overlap (line 178) | def _interval_overlap(interval_a, interval_b): function _sigmoid (line 193) | def _sigmoid(x): function bbox_iou (line 196) | def bbox_iou(box1, box2): function do_nms (line 210) | def do_nms(boxes, nms_thresh): function decode_netout (line 230) | def decode_netout(netout, anchors, obj_thresh, nms_thresh, net_h, net_w): function preprocess_input (line 272) | def preprocess_input(image, input_shape): function retrieve_yolo_detections (line 294) | def retrieve_yolo_detections(yolo_result, anchors, min_probability, nms_... function draw_boxes (line 344) | def draw_boxes(image, box_points, draw_box, label, percentage_probabilit... FILE: imageai_tf_deprecated/Detection/YOLO/yolov3.py class YoloLayer (line 14) | class YoloLayer(Layer): method __init__ (line 15) | def __init__(self, anchors, max_grid, batch_size, warmup_batches, igno... method build (line 37) | def build(self, input_shape): method call (line 40) | def call(self, x): method compute_output_shape (line 189) | def compute_output_shape(self, input_shape): function dummy_loss (line 194) | def dummy_loss(y_true, y_pred): function NetworkConv2D_BN_Leaky (line 197) | def NetworkConv2D_BN_Leaky(input, channels, kernel_size, kernel_regulari... function residual_block (line 204) | def residual_block(input, channels, num_blocks): function darknet (line 215) | def darknet(input): function last_layers (line 226) | def last_layers(input, channels_in, channels_out, layer_name=""): function yolov3_base (line 241) | def yolov3_base(input, num_anchors, num_classes): function yolov3_main (line 261) | def yolov3_main(input, num_anchors, num_classes): function yolov3_train (line 268) | def yolov3_train(num_classes, function tiny_yolov3_main (line 330) | def tiny_yolov3_main(input, num_anchors, num_classes): function dummy_loss (line 360) | def dummy_loss(y_true, y_pred): FILE: imageai_tf_deprecated/Detection/__init__.py class ObjectDetection (line 21) | class ObjectDetection: method __init__ (line 37) | def __init__(self): method setModelTypeAsRetinaNet (line 85) | def setModelTypeAsRetinaNet(self): method setModelTypeAsYOLOv3 (line 93) | def setModelTypeAsYOLOv3(self): method setModelTypeAsTinyYOLOv3 (line 102) | def setModelTypeAsTinyYOLOv3(self): method setModelPath (line 111) | def setModelPath(self, model_path): method loadModel (line 123) | def loadModel(self, detection_speed="normal"): method detectObjectsFromImage (line 200) | def detectObjectsFromImage(self, input_image="", output_image_path="",... method CustomObjects (line 394) | def CustomObjects(self, person=False, bicycle=False, car=False, motorc... method detectCustomObjectsFromImage (line 464) | def detectCustomObjectsFromImage(self, input_image="", output_image_pa... class VideoObjectDetection (line 485) | class VideoObjectDetection: method __init__ (line 502) | def __init__(self): method setModelTypeAsRetinaNet (line 539) | def setModelTypeAsRetinaNet(self): method setModelTypeAsYOLOv3 (line 547) | def setModelTypeAsYOLOv3(self): method setModelTypeAsTinyYOLOv3 (line 555) | def setModelTypeAsTinyYOLOv3(self): method setModelPath (line 563) | def setModelPath(self, model_path): method loadModel (line 575) | def loadModel(self, detection_speed="normal"): method detectObjectsFromVideo (line 605) | def detectObjectsFromVideo(self, input_file_path="", camera_input=None... method CustomObjects (line 888) | def CustomObjects(self, person=False, bicycle=False, car=False, motorc... method detectCustomObjectsFromVideo (line 958) | def detectCustomObjectsFromVideo(self, input_file_path="", camera_inpu... FILE: imageai_tf_deprecated/Detection/keras_retinanet/backend/backend.py function bbox_transform_inv (line 21) | def bbox_transform_inv(boxes, deltas, mean=None, std=None): function shift (line 55) | def shift(shape, stride, anchors): function map_fn (line 88) | def map_fn(*args, **kwargs): function resize_images (line 107) | def resize_images(images, size, method='bilinear', align_corners=False): FILE: imageai_tf_deprecated/Detection/keras_retinanet/bin/convert_model.py function parse_args (line 36) | def parse_args(args): function main (line 53) | def main(args=None): FILE: imageai_tf_deprecated/Detection/keras_retinanet/bin/debug.py function create_generator (line 52) | def create_generator(args): function parse_args (line 140) | def parse_args(args): function run (line 191) | def run(generator, args, anchor_params, pyramid_levels): function make_output_path (line 267) | def make_output_path(output_dir, image_path, flatten = False): function main (line 289) | def main(args=None): FILE: imageai_tf_deprecated/Detection/keras_retinanet/bin/evaluate.py function create_generator (line 38) | def create_generator(args, preprocess_image): function parse_args (line 81) | def parse_args(args): function main (line 116) | def main(args=None): FILE: imageai_tf_deprecated/Detection/keras_retinanet/bin/train.py function makedirs (line 53) | def makedirs(path): function model_with_weights (line 64) | def model_with_weights(model, weights, skip_mismatch): function create_models (line 77) | def create_models(backbone_retinanet, num_classes, weights, multi_gpu=0, function create_callbacks (line 133) | def create_callbacks(model, training_model, prediction_model, validation... function create_generators (line 221) | def create_generators(args, preprocess_image): function check_args (line 359) | def check_args(parsed_args): function parse_args (line 390) | def parse_args(args): function main (line 462) | def main(args=None): FILE: imageai_tf_deprecated/Detection/keras_retinanet/callbacks/coco.py class CocoEval (line 21) | class CocoEval(keras.callbacks.Callback): method __init__ (line 24) | def __init__(self, generator, tensorboard=None, threshold=0.05): method on_epoch_end (line 38) | def on_epoch_end(self, epoch, logs=None): FILE: imageai_tf_deprecated/Detection/keras_retinanet/callbacks/common.py class RedirectModel (line 4) | class RedirectModel(keras.callbacks.Callback): method __init__ (line 19) | def __init__(self, method on_epoch_begin (line 27) | def on_epoch_begin(self, epoch, logs=None): method on_epoch_end (line 30) | def on_epoch_end(self, epoch, logs=None): method on_batch_begin (line 33) | def on_batch_begin(self, batch, logs=None): method on_batch_end (line 36) | def on_batch_end(self, batch, logs=None): method on_train_begin (line 39) | def on_train_begin(self, logs=None): method on_train_end (line 45) | def on_train_end(self, logs=None): FILE: imageai_tf_deprecated/Detection/keras_retinanet/callbacks/eval.py class Evaluate (line 21) | class Evaluate(keras.callbacks.Callback): method __init__ (line 25) | def __init__( method on_epoch_end (line 59) | def on_epoch_end(self, epoch, logs=None): FILE: imageai_tf_deprecated/Detection/keras_retinanet/initializers.py class PriorProbability (line 22) | class PriorProbability(keras.initializers.Initializer): method __init__ (line 26) | def __init__(self, probability=0.01): method get_config (line 29) | def get_config(self): method __call__ (line 34) | def __call__(self, shape, dtype=None): FILE: imageai_tf_deprecated/Detection/keras_retinanet/layers/_misc.py class Anchors (line 25) | class Anchors(keras.layers.Layer): method __init__ (line 29) | def __init__(self, size, stride, ratios=None, scales=None, *args, **kw... method call (line 61) | def call(self, inputs, **kwargs): method compute_output_shape (line 74) | def compute_output_shape(self, input_shape): method get_config (line 85) | def get_config(self): class UpsampleLike (line 97) | class UpsampleLike(keras.layers.Layer): method call (line 101) | def call(self, inputs, **kwargs): method compute_output_shape (line 112) | def compute_output_shape(self, input_shape): class RegressBoxes (line 119) | class RegressBoxes(keras.layers.Layer): method __init__ (line 123) | def __init__(self, mean=None, std=None, *args, **kwargs): method call (line 149) | def call(self, inputs, **kwargs): method compute_output_shape (line 153) | def compute_output_shape(self, input_shape): method get_config (line 156) | def get_config(self): class ClipBoxes (line 166) | class ClipBoxes(keras.layers.Layer): method call (line 169) | def call(self, inputs, **kwargs): method compute_output_shape (line 185) | def compute_output_shape(self, input_shape): FILE: imageai_tf_deprecated/Detection/keras_retinanet/layers/filter_detections.py function filter_detections (line 22) | def filter_detections( class FilterDetections (line 116) | class FilterDetections(keras.layers.Layer): method __init__ (line 120) | def __init__( method call (line 148) | def call(self, inputs, **kwargs): method compute_output_shape (line 189) | def compute_output_shape(self, input_shape): method compute_mask (line 207) | def compute_mask(self, inputs, mask=None): method get_config (line 212) | def get_config(self): FILE: imageai_tf_deprecated/Detection/keras_retinanet/losses.py function focal (line 21) | def focal(alpha=0.25, gamma=2.0, cutoff=0.5): function smooth_l1 (line 71) | def smooth_l1(sigma=3.0): FILE: imageai_tf_deprecated/Detection/keras_retinanet/models/__init__.py class Backbone (line 5) | class Backbone(object): method __init__ (line 8) | def __init__(self, backbone): method retinanet (line 27) | def retinanet(self, *args, **kwargs): method download_imagenet (line 32) | def download_imagenet(self): method validate (line 37) | def validate(self): method preprocess_image (line 42) | def preprocess_image(self, inputs): function backbone (line 49) | def backbone(backbone_name): function load_model (line 70) | def load_model(filepath, backbone_name='resnet50'): function convert_model (line 90) | def convert_model(model, nms=True, class_specific_filter=True, anchor_pa... function assert_training_model (line 111) | def assert_training_model(model): function check_training_model (line 118) | def check_training_model(model): FILE: imageai_tf_deprecated/Detection/keras_retinanet/models/densenet.py class DenseNetBackbone (line 31) | class DenseNetBackbone(Backbone): method retinanet (line 35) | def retinanet(self, *args, **kwargs): method download_imagenet (line 40) | def download_imagenet(self): method validate (line 57) | def validate(self): method preprocess_image (line 65) | def preprocess_image(self, inputs): function densenet_retinanet (line 71) | def densenet_retinanet(num_classes, backbone='densenet121', inputs=None,... FILE: imageai_tf_deprecated/Detection/keras_retinanet/models/effnet.py class EfficientNetBackbone (line 24) | class EfficientNetBackbone(Backbone): method __init__ (line 28) | def __init__(self, backbone): method retinanet (line 32) | def retinanet(self, *args, **kwargs): method download_imagenet (line 37) | def download_imagenet(self): method validate (line 49) | def validate(self): method preprocess_image (line 59) | def preprocess_image(self, inputs): function effnet_retinanet (line 65) | def effnet_retinanet(num_classes, backbone='EfficientNetB0', inputs=None... function EfficientNetB0_retinanet (line 130) | def EfficientNetB0_retinanet(num_classes, inputs=None, **kwargs): function EfficientNetB1_retinanet (line 134) | def EfficientNetB1_retinanet(num_classes, inputs=None, **kwargs): function EfficientNetB2_retinanet (line 138) | def EfficientNetB2_retinanet(num_classes, inputs=None, **kwargs): function EfficientNetB3_retinanet (line 142) | def EfficientNetB3_retinanet(num_classes, inputs=None, **kwargs): function EfficientNetB4_retinanet (line 146) | def EfficientNetB4_retinanet(num_classes, inputs=None, **kwargs): function EfficientNetB5_retinanet (line 150) | def EfficientNetB5_retinanet(num_classes, inputs=None, **kwargs): function EfficientNetB6_retinanet (line 154) | def EfficientNetB6_retinanet(num_classes, inputs=None, **kwargs): function EfficientNetB7_retinanet (line 158) | def EfficientNetB7_retinanet(num_classes, inputs=None, **kwargs): FILE: imageai_tf_deprecated/Detection/keras_retinanet/models/mobilenet.py class MobileNetBackbone (line 24) | class MobileNetBackbone(Backbone): method retinanet (line 30) | def retinanet(self, *args, **kwargs): method download_imagenet (line 35) | def download_imagenet(self): method validate (line 64) | def validate(self): method preprocess_image (line 72) | def preprocess_image(self, inputs): function mobilenet_retinanet (line 78) | def mobilenet_retinanet(num_classes, backbone='mobilenet224_1.0', inputs... FILE: imageai_tf_deprecated/Detection/keras_retinanet/models/resnet.py class ResNetBackbone (line 26) | class ResNetBackbone(Backbone): method __init__ (line 30) | def __init__(self, backbone): method retinanet (line 34) | def retinanet(self, *args, **kwargs): method download_imagenet (line 39) | def download_imagenet(self): method validate (line 62) | def validate(self): method preprocess_image (line 71) | def preprocess_image(self, inputs): function resnet_retinanet (line 77) | def resnet_retinanet(num_classes, backbone='resnet50', inputs=None, modi... function resnet50_retinanet (line 122) | def resnet50_retinanet(num_classes, inputs=None, **kwargs): function resnet101_retinanet (line 126) | def resnet101_retinanet(num_classes, inputs=None, **kwargs): function resnet152_retinanet (line 130) | def resnet152_retinanet(num_classes, inputs=None, **kwargs): FILE: imageai_tf_deprecated/Detection/keras_retinanet/models/retinanet.py function default_classification_model (line 24) | def default_classification_model( function default_regression_model (line 82) | def default_regression_model(num_values, num_anchors, pyramid_feature_si... function __create_pyramid_features (line 127) | def __create_pyramid_features(backbone_layers, pyramid_levels, feature_s... function default_submodels (line 184) | def default_submodels(num_classes, num_anchors): function __build_model_pyramid (line 202) | def __build_model_pyramid(name, model, features): function __build_pyramid (line 216) | def __build_pyramid(models, features): function __build_anchors (line 229) | def __build_anchors(anchor_parameters, features): function retinanet (line 257) | def retinanet( function retinanet_bbox (line 316) | def retinanet_bbox( FILE: imageai_tf_deprecated/Detection/keras_retinanet/models/senet.py class SeBackbone (line 24) | class SeBackbone(Backbone): method __init__ (line 28) | def __init__(self, backbone): method retinanet (line 32) | def retinanet(self, *args, **kwargs): method download_imagenet (line 37) | def download_imagenet(self): method validate (line 52) | def validate(self): method preprocess_image (line 62) | def preprocess_image(self, inputs): function senet_retinanet (line 68) | def senet_retinanet(num_classes, backbone='seresnext50', inputs=None, mo... function seresnet18_retinanet (line 132) | def seresnet18_retinanet(num_classes, inputs=None, **kwargs): function seresnet34_retinanet (line 136) | def seresnet34_retinanet(num_classes, inputs=None, **kwargs): function seresnet50_retinanet (line 140) | def seresnet50_retinanet(num_classes, inputs=None, **kwargs): function seresnet101_retinanet (line 144) | def seresnet101_retinanet(num_classes, inputs=None, **kwargs): function seresnet152_retinanet (line 148) | def seresnet152_retinanet(num_classes, inputs=None, **kwargs): function seresnext50_retinanet (line 152) | def seresnext50_retinanet(num_classes, inputs=None, **kwargs): function seresnext101_retinanet (line 156) | def seresnext101_retinanet(num_classes, inputs=None, **kwargs): function senet154_retinanet (line 160) | def senet154_retinanet(num_classes, inputs=None, **kwargs): FILE: imageai_tf_deprecated/Detection/keras_retinanet/models/vgg.py class VGGBackbone (line 25) | class VGGBackbone(Backbone): method retinanet (line 29) | def retinanet(self, *args, **kwargs): method download_imagenet (line 34) | def download_imagenet(self): method validate (line 54) | def validate(self): method preprocess_image (line 62) | def preprocess_image(self, inputs): function vgg_retinanet (line 68) | def vgg_retinanet(num_classes, backbone='vgg16', inputs=None, modifier=N... FILE: imageai_tf_deprecated/Detection/keras_retinanet/preprocessing/coco.py class CocoGenerator (line 26) | class CocoGenerator(Generator): method __init__ (line 32) | def __init__(self, data_dir, set_name, **kwargs): method load_classes (line 48) | def load_classes(self): method size (line 68) | def size(self): method num_classes (line 73) | def num_classes(self): method has_label (line 78) | def has_label(self, label): method has_name (line 83) | def has_name(self, name): method name_to_label (line 88) | def name_to_label(self, name): method label_to_name (line 93) | def label_to_name(self, label): method coco_label_to_label (line 98) | def coco_label_to_label(self, coco_label): method coco_label_to_name (line 104) | def coco_label_to_name(self, coco_label): method label_to_coco_label (line 109) | def label_to_coco_label(self, label): method image_path (line 114) | def image_path(self, image_index): method image_aspect_ratio (line 121) | def image_aspect_ratio(self, image_index): method load_image (line 127) | def load_image(self, image_index): method load_annotations (line 133) | def load_annotations(self, image_index): FILE: imageai_tf_deprecated/Detection/keras_retinanet/preprocessing/csv_generator.py function _parse (line 31) | def _parse(value, function, fmt): function _read_classes (line 45) | def _read_classes(csv_reader): function _read_annotations (line 64) | def _read_annotations(csv_reader, classes): function _open_for_csv (line 102) | def _open_for_csv(path): class CSVGenerator (line 114) | class CSVGenerator(Generator): method __init__ (line 120) | def __init__( method size (line 163) | def size(self): method num_classes (line 168) | def num_classes(self): method has_label (line 173) | def has_label(self, label): method has_name (line 178) | def has_name(self, name): method name_to_label (line 183) | def name_to_label(self, name): method label_to_name (line 188) | def label_to_name(self, label): method image_path (line 193) | def image_path(self, image_index): method image_aspect_ratio (line 198) | def image_aspect_ratio(self, image_index): method load_image (line 205) | def load_image(self, image_index): method load_annotations (line 210) | def load_annotations(self, image_index): FILE: imageai_tf_deprecated/Detection/keras_retinanet/preprocessing/generator.py class Generator (line 39) | class Generator(keras.utils.Sequence): method __init__ (line 43) | def __init__( method on_epoch_end (line 95) | def on_epoch_end(self): method size (line 99) | def size(self): method num_classes (line 104) | def num_classes(self): method has_label (line 109) | def has_label(self, label): method has_name (line 114) | def has_name(self, name): method name_to_label (line 119) | def name_to_label(self, name): method label_to_name (line 124) | def label_to_name(self, label): method image_aspect_ratio (line 129) | def image_aspect_ratio(self, image_index): method image_path (line 134) | def image_path(self, image_index): method load_image (line 139) | def load_image(self, image_index): method load_annotations (line 144) | def load_annotations(self, image_index): method load_annotations_group (line 149) | def load_annotations_group(self, group): method filter_annotations (line 160) | def filter_annotations(self, image_group, annotations_group, group): method load_image_group (line 187) | def load_image_group(self, group): method random_visual_effect_group_entry (line 192) | def random_visual_effect_group_entry(self, image, annotations): method random_visual_effect_group (line 200) | def random_visual_effect_group(self, image_group, annotations_group): method random_transform_group_entry (line 217) | def random_transform_group_entry(self, image, annotations, transform=N... method random_transform_group (line 235) | def random_transform_group(self, image_group, annotations_group): method resize_image (line 247) | def resize_image(self, image): method preprocess_group_entry (line 255) | def preprocess_group_entry(self, image, annotations): method preprocess_group (line 272) | def preprocess_group(self, image_group, annotations_group): method group_images (line 283) | def group_images(self): method compute_inputs (line 296) | def compute_inputs(self, image_group): method generate_anchors (line 314) | def generate_anchors(self, image_shape): method compute_targets (line 324) | def compute_targets(self, image_group, annotations_group): method compute_input_output (line 340) | def compute_input_output(self, group): method __len__ (line 367) | def __len__(self): method __getitem__ (line 374) | def __getitem__(self, index): FILE: imageai_tf_deprecated/Detection/keras_retinanet/preprocessing/kitti.py class KittiGenerator (line 39) | class KittiGenerator(Generator): method __init__ (line 45) | def __init__( method size (line 108) | def size(self): method num_classes (line 113) | def num_classes(self): method has_label (line 118) | def has_label(self, label): method has_name (line 123) | def has_name(self, name): method name_to_label (line 128) | def name_to_label(self, name): method label_to_name (line 133) | def label_to_name(self, label): method image_aspect_ratio (line 138) | def image_aspect_ratio(self, image_index): method image_path (line 145) | def image_path(self, image_index): method load_image (line 150) | def load_image(self, image_index): method load_annotations (line 155) | def load_annotations(self, image_index): FILE: imageai_tf_deprecated/Detection/keras_retinanet/preprocessing/open_images.py function load_hierarchy (line 29) | def load_hierarchy(metadata_dir, version='v4'): function load_hierarchy_children (line 45) | def load_hierarchy_children(hierarchy): function find_hierarchy_parent (line 58) | def find_hierarchy_parent(hierarchy, parent_cls): function get_labels (line 70) | def get_labels(metadata_dir, version='v4'): function generate_images_annotations_json (line 110) | def generate_images_annotations_json(main_dir, metadata_dir, subset, cls... class OpenImagesGenerator (line 213) | class OpenImagesGenerator(Generator): method __init__ (line 214) | def __init__( method __filter_data (line 256) | def __filter_data(self, id_to_labels, cls_index, labels_filter=None, p... method size (line 321) | def size(self): method num_classes (line 324) | def num_classes(self): method has_label (line 327) | def has_label(self, label): method has_name (line 332) | def has_name(self, name): method name_to_label (line 337) | def name_to_label(self, name): method label_to_name (line 340) | def label_to_name(self, label): method image_aspect_ratio (line 343) | def image_aspect_ratio(self, image_index): method image_path (line 348) | def image_path(self, image_index): method load_image (line 352) | def load_image(self, image_index): method load_annotations (line 355) | def load_annotations(self, image_index): FILE: imageai_tf_deprecated/Detection/keras_retinanet/preprocessing/pascal_voc.py function _findNode (line 54) | def _findNode(parent, name, debug_name=None, parse=None): class PascalVocGenerator (line 69) | class PascalVocGenerator(Generator): method __init__ (line 75) | def __init__( method size (line 105) | def size(self): method num_classes (line 110) | def num_classes(self): method has_label (line 115) | def has_label(self, label): method has_name (line 120) | def has_name(self, name): method name_to_label (line 125) | def name_to_label(self, name): method label_to_name (line 130) | def label_to_name(self, label): method image_aspect_ratio (line 135) | def image_aspect_ratio(self, image_index): method image_path (line 142) | def image_path(self, image_index): method load_image (line 147) | def load_image(self, image_index): method __parse_annotation (line 152) | def __parse_annotation(self, element): method __parse_annotations (line 173) | def __parse_annotations(self, xml_root): method load_annotations (line 193) | def load_annotations(self, image_index): FILE: imageai_tf_deprecated/Detection/keras_retinanet/utils/anchors.py class AnchorParameters (line 23) | class AnchorParameters: method __init__ (line 32) | def __init__(self, sizes, strides, ratios, scales): method num_anchors (line 38) | def num_anchors(self): function anchor_targets_bbox (line 53) | def anchor_targets_bbox( function layer_shapes (line 119) | def layer_shapes(image_shape, model): function make_shapes_callback (line 147) | def make_shapes_callback(model): function guess_shapes (line 158) | def guess_shapes(image_shape, pyramid_levels): function anchors_for_shape (line 173) | def anchors_for_shape( function shift (line 215) | def shift(shape, stride, anchors): function generate_anchors (line 247) | def generate_anchors(base_size=16, ratios=None, scales=None): function bbox_transform (line 281) | def bbox_transform(anchors, gt_boxes, mean=None, std=None): FILE: imageai_tf_deprecated/Detection/keras_retinanet/utils/coco_eval.py function evaluate_coco (line 27) | def evaluate_coco(generator, model, threshold=0.05): FILE: imageai_tf_deprecated/Detection/keras_retinanet/utils/colors.py function label_color (line 4) | def label_color(label): FILE: imageai_tf_deprecated/Detection/keras_retinanet/utils/config.py function read_config_file (line 23) | def read_config_file(config_path): function parse_anchor_parameters (line 44) | def parse_anchor_parameters(config): function parse_pyramid_levels (line 54) | def parse_pyramid_levels(config): FILE: imageai_tf_deprecated/Detection/keras_retinanet/utils/eval.py function _compute_ap (line 30) | def _compute_ap(recall, precision): function _get_detections (line 59) | def _get_detections(generator, model, score_threshold=0.05, max_detectio... function _get_annotations (line 126) | def _get_annotations(generator): function evaluate (line 153) | def evaluate( FILE: imageai_tf_deprecated/Detection/keras_retinanet/utils/gpu.py function setup_gpu (line 20) | def setup_gpu(gpu_id): FILE: imageai_tf_deprecated/Detection/keras_retinanet/utils/image.py function read_image_bgr (line 25) | def read_image_bgr(path): function preprocess_image (line 36) | def preprocess_image(x, mode='caffe'): function adjust_transform_for_image (line 64) | def adjust_transform_for_image(transform, image, relative_translation): class TransformParameters (line 84) | class TransformParameters: method __init__ (line 94) | def __init__( method cvBorderMode (line 106) | def cvBorderMode(self): method cvInterpolation (line 116) | def cvInterpolation(self): function apply_transform (line 129) | def apply_transform(matrix, image, params): function compute_resize_scale (line 154) | def compute_resize_scale(image_shape, min_side=800, max_side=1333): function resize_image (line 180) | def resize_image(img, min_side=800, max_side=1333): function _uniform (line 199) | def _uniform(val_range): function _check_range (line 208) | def _check_range(val_range, min_val=None, max_val=None): function _clip (line 224) | def _clip(image): class VisualEffect (line 234) | class VisualEffect: method __init__ (line 244) | def __init__( method __call__ (line 256) | def __call__(self, image): function random_visual_effect_generator (line 282) | def random_visual_effect_generator( function adjust_contrast (line 315) | def adjust_contrast(image, factor): function adjust_brightness (line 326) | def adjust_brightness(image, delta): function adjust_hue (line 336) | def adjust_hue(image, delta): function adjust_saturation (line 348) | def adjust_saturation(image, factor): FILE: imageai_tf_deprecated/Detection/keras_retinanet/utils/model.py function freeze (line 18) | def freeze(model): FILE: imageai_tf_deprecated/Detection/keras_retinanet/utils/tf_version.py function tf_version (line 26) | def tf_version(): function tf_version_ok (line 34) | def tf_version_ok(minimum_tf_version=MINIMUM_TF_VERSION, blacklisted=BLA... function assert_tf_version (line 40) | def assert_tf_version(minimum_tf_version=MINIMUM_TF_VERSION, blacklisted... function check_tf_version (line 48) | def check_tf_version(): FILE: imageai_tf_deprecated/Detection/keras_retinanet/utils/transform.py function colvec (line 22) | def colvec(*args): function transform_aabb (line 27) | def transform_aabb(transform, aabb): function _random_vector (line 57) | def _random_vector(min, max, prng=DEFAULT_PRNG): function rotation (line 70) | def rotation(angle): function random_rotation (line 84) | def random_rotation(min, max, prng=DEFAULT_PRNG): function translation (line 96) | def translation(translation): function random_translation (line 110) | def random_translation(min, max, prng=DEFAULT_PRNG): function shear (line 122) | def shear(angle): function random_shear (line 136) | def random_shear(min, max, prng=DEFAULT_PRNG): function scaling (line 148) | def scaling(factor): function random_scaling (line 162) | def random_scaling(min, max, prng=DEFAULT_PRNG): function random_flip (line 174) | def random_flip(flip_x_chance, flip_y_chance, prng=DEFAULT_PRNG): function change_transform_origin (line 189) | def change_transform_origin(transform, center): function random_transform (line 202) | def random_transform( function random_transform_generator (line 252) | def random_transform_generator(prng=None, **kwargs): FILE: imageai_tf_deprecated/Detection/keras_retinanet/utils/visualization.py function draw_box (line 23) | def draw_box(image, box, color, thickness=2): function draw_caption (line 36) | def draw_caption(image, box, caption): function draw_boxes (line 49) | def draw_boxes(image, boxes, color, thickness=2): function draw_detections (line 62) | def draw_detections(image, boxes, scores, labels, color=None, label_to_n... function draw_annotations (line 85) | def draw_annotations(image, annotations, color=(0, 255, 0), label_to_nam... FILE: imageai_tf_deprecated/Prediction/Custom/__init__.py class ModelTraining (line 7) | class ModelTraining(ClassificationModelTrainer): method __call__ (line 12) | def __call__(self): class CustomImagePrediction (line 15) | class CustomImagePrediction(CustomImageClassification): method __call__ (line 21) | def __call__(self): FILE: imageai_tf_deprecated/Prediction/Custom/custom_utils.py function preprocess_input (line 7) | def preprocess_input(x): function decode_predictions (line 25) | def decode_predictions(preds, top=5, model_json=""): FILE: imageai_tf_deprecated/Prediction/__init__.py class ImagePrediction (line 5) | class ImagePrediction(ImageClassification): method __call__ (line 11) | def __call__(self): FILE: imageai_tf_deprecated/Prediction/imagenet_utils.py function preprocess_input (line 5) | def preprocess_input(x): function decode_predictions (line 27) | def decode_predictions(preds, top=5): FILE: scripts/pascal_voc_to_yolo.py function convert (line 15) | def convert(size, box): function convert_annotation (line 28) | def convert_annotation(input_ann_path): function main (line 56) | def main(dataset_dir: str): FILE: test/test_custom_classification.py function test_recognition_model_mobilenetv2 (line 21) | def test_recognition_model_mobilenetv2(image_input): function test_recognition_model_resnet (line 44) | def test_recognition_model_resnet(image_input): function test_recognition_model_inceptionv3 (line 66) | def test_recognition_model_inceptionv3(image_input): function test_recognition_model_densenet (line 88) | def test_recognition_model_densenet(image_input): FILE: test/test_custom_classification_training.py function test_resnet50_training (line 35) | def test_resnet50_training(transfer_learning): function test_densenet121_training (line 78) | def test_densenet121_training(transfer_learning): function test_inceptionv3_training (line 121) | def test_inceptionv3_training(transfer_learning): function test_mobilenetv2_training (line 163) | def test_mobilenetv2_training(transfer_learning): FILE: test/test_custom_detection_training.py function delete_cache (line 22) | def delete_cache(dirs: list): function test_yolov3_training (line 37) | def test_yolov3_training(transfer_learning): function test_tiny_yolov3_training (line 66) | def test_tiny_yolov3_training(transfer_learning): FILE: test/test_custom_object_detection.py function delete_cache (line 17) | def delete_cache(paths: List[str]): function test_object_detection_yolov3 (line 35) | def test_object_detection_yolov3(input_image, output_type, extract_objec... function test_object_detection_tiny_yolov3 (line 103) | def test_object_detection_tiny_yolov3(input_image, output_type, extract_... FILE: test/test_custom_video_detection.py class CallbackFunctions (line 18) | class CallbackFunctions: method forFrame (line 19) | def forFrame(frame_number, output_array, output_count, detected_frame): method forSecond (line 33) | def forSecond(second_number, output_arrays, count_arrays, average_outp... function delete_cache (line 57) | def delete_cache(files: List[str]): function test_video_detection_yolov3 (line 65) | def test_video_detection_yolov3(): function test_video_detection_tiny_yolov3 (line 81) | def test_video_detection_tiny_yolov3(): function test_video_detection_yolo_analysis (line 97) | def test_video_detection_yolo_analysis(): FILE: test/test_image_classification.py function test_recognition_model_mobilenetv2 (line 21) | def test_recognition_model_mobilenetv2(image_input): function test_recognition_model_resnet (line 43) | def test_recognition_model_resnet(image_input): function test_recognition_model_inceptionv3 (line 64) | def test_recognition_model_inceptionv3(image_input): function test_recognition_model_densenet (line 85) | def test_recognition_model_densenet(image_input): FILE: test/test_object_detection.py function delete_cache (line 16) | def delete_cache(paths: List[str]): function test_object_detection_retinanet (line 35) | def test_object_detection_retinanet(input_image, output_type, extract_ob... function test_object_detection_yolov3 (line 102) | def test_object_detection_yolov3(input_image, output_type, extract_objec... function test_object_detection_tiny_yolov3 (line 170) | def test_object_detection_tiny_yolov3(input_image, output_type, extract_... function test_object_detection_retinanet_custom_objects (line 237) | def test_object_detection_retinanet_custom_objects(input_image): function test_object_detection_yolov3_custom_objects (line 263) | def test_object_detection_yolov3_custom_objects(input_image): function test_object_detection_tiny_yolov3_custom_objects (line 289) | def test_object_detection_tiny_yolov3_custom_objects(input_image): FILE: test/test_video_object_detection.py class CallbackFunctions (line 18) | class CallbackFunctions: method forFrame (line 19) | def forFrame(frame_number, output_array, output_count, detected_frame): method forSecond (line 33) | def forSecond(second_number, output_arrays, count_arrays, average_outp... function delete_cache (line 57) | def delete_cache(files: List[str]): function test_video_detection_retinanet (line 63) | def test_video_detection_retinanet(): function test_video_detection_retinanet_custom_objects (line 79) | def test_video_detection_retinanet_custom_objects(): function test_video_detection_yolov3 (line 103) | def test_video_detection_yolov3(): function test_video_detection_tiny_yolov3 (line 119) | def test_video_detection_tiny_yolov3(): function test_video_detection_retinanet_analysis (line 134) | def test_video_detection_retinanet_analysis():