def yolo5_postprocess_np(yolo_outputs,
image_shape,
anchors,
num_classes,
model_image_size,
max_boxes=100,
confidence=0.1,
iou_threshold=0.4,
elim_grid_sense=True):
predictions = yolo5_decode(yolo_outputs,
anchors,
num_classes,
input_dims=model_image_size,
elim_grid_sense=elim_grid_sense)
predictions = yolo_correct_boxes(predictions, image_shape,
model_image_size)
boxes, classes, scores = yolo_handle_predictions(
predictions,
image_shape,
max_boxes=max_boxes,
confidence=confidence,
iou_threshold=iou_threshold,
use_cluster_nms=True)
boxes = yolo_adjust_boxes(boxes, image_shape)
return boxes, classes, scores
def yolo3_postprocess_np(yolo_outputs,
image_shape,
anchors,
num_classes,
model_input_shape,
max_boxes=100,
confidence=0.1,
iou_threshold=0.4,
elim_grid_sense=False):
# here we sort the prediction tensor list with grid size (e.g. 19/38/76)
# to make sure it matches with anchors order
yolo_outputs.sort(key=lambda x: x.shape[1])
predictions = yolo3_decode(yolo_outputs,
anchors,
num_classes,
input_shape=model_input_shape,
elim_grid_sense=elim_grid_sense)
predictions = yolo_correct_boxes(predictions, image_shape,
model_input_shape)
boxes, classes, scores = yolo_handle_predictions(
predictions,
image_shape,
num_classes,
max_boxes=max_boxes,
confidence=confidence,
iou_threshold=iou_threshold)
boxes = yolo_adjust_boxes(boxes, image_shape)
return boxes, classes, scores
def yolo2_postprocess_np(yolo_outputs,
image_shape,
anchors,
num_classes,
model_input_shape,
max_boxes=100,
confidence=0.1,
iou_threshold=0.4,
elim_grid_sense=False):
scale_x_y = 1.05 if elim_grid_sense else None
predictions = yolo_decode(yolo_outputs,
anchors,
num_classes,
input_shape=model_input_shape,
scale_x_y=scale_x_y,
use_softmax=True)
predictions = yolo_correct_boxes(predictions, image_shape,
model_input_shape)
boxes, classes, scores = yolo_handle_predictions(
predictions,
image_shape,
num_classes,
max_boxes=max_boxes,
confidence=confidence,
iou_threshold=iou_threshold)
boxes = yolo_adjust_boxes(boxes, image_shape)
return boxes, classes, scores
def yolo2_postprocess_np(yolo_outputs, image_shape, anchors, num_classes, model_image_size, max_boxes=100, confidence=0.1, iou_threshold=0.4):
predictions = yolo_head(yolo_outputs, anchors, num_classes, input_dims=model_image_size, use_softmax=True)
predictions = yolo_correct_boxes(predictions, image_shape, model_image_size)
boxes, classes, scores = yolo_handle_predictions(predictions,
image_shape,
max_boxes=max_boxes,
confidence=confidence,
iou_threshold=iou_threshold)
boxes = yolo_adjust_boxes(boxes, image_shape)
return boxes, classes, scores
