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Python源码示例：keras.iou()

示例1

def get_map(pred, gt, f):
	T = {}
	P = {}
	fx, fy = f

	for bbox in gt:
		bbox['bbox_matched'] = False

	pred_probs = np.array([s['prob'] for s in pred])
	box_idx_sorted_by_prob = np.argsort(pred_probs)[::-1]

	for box_idx in box_idx_sorted_by_prob:
		pred_box = pred[box_idx]
		pred_class = pred_box['class']
		pred_x1 = pred_box['x1']
		pred_x2 = pred_box['x2']
		pred_y1 = pred_box['y1']
		pred_y2 = pred_box['y2']
		pred_prob = pred_box['prob']
		if pred_class not in P:
			P[pred_class] = []
			T[pred_class] = []
		P[pred_class].append(pred_prob)
		found_match = False

		for gt_box in gt:
			gt_class = gt_box['class']
			gt_x1 = gt_box['x1']/fx
			gt_x2 = gt_box['x2']/fx
			gt_y1 = gt_box['y1']/fy
			gt_y2 = gt_box['y2']/fy
			gt_seen = gt_box['bbox_matched']
			if gt_class != pred_class:
				continue
			if gt_seen:
				continue
			iou = data_generators.iou((pred_x1, pred_y1, pred_x2, pred_y2), (gt_x1, gt_y1, gt_x2, gt_y2))
			if iou >= 0.5:
				found_match = True
				gt_box['bbox_matched'] = True
				break
			else:
				continue

		T[pred_class].append(int(found_match))

	for gt_box in gt:
		if not gt_box['bbox_matched'] and not gt_box['difficult']:
			if gt_box['class'] not in P:
				P[gt_box['class']] = []
				T[gt_box['class']] = []

			T[gt_box['class']].append(1)
			P[gt_box['class']].append(0)

	#import pdb
	#pdb.set_trace()
	return T, P

示例2

def get_map(pred, gt, f):
	T = {}
	P = {}
	fx, fy = f

	for bbox in gt:
		bbox['bbox_matched'] = False

	pred_probs = np.array([s['prob'] for s in pred])
	box_idx_sorted_by_prob = np.argsort(pred_probs)[::-1]

	for box_idx in box_idx_sorted_by_prob:
		pred_box = pred[box_idx]
		pred_class = pred_box['class']
		pred_x1 = pred_box['x1']
		pred_x2 = pred_box['x2']
		pred_y1 = pred_box['y1']
		pred_y2 = pred_box['y2']
		pred_prob = pred_box['prob']
		if pred_class not in P:
			P[pred_class] = []
			T[pred_class] = []
		P[pred_class].append(pred_prob)
		found_match = False

		for gt_box in gt:
			gt_class = gt_box['class']
			gt_x1 = gt_box['x1']/fx
			gt_x2 = gt_box['x2']/fx
			gt_y1 = gt_box['y1']/fy
			gt_y2 = gt_box['y2']/fy
			gt_seen = gt_box['bbox_matched']
			if gt_class != pred_class:
				continue
			if gt_seen:
				continue
			iou = data_generators.iou((pred_x1, pred_y1, pred_x2, pred_y2), (gt_x1, gt_y1, gt_x2, gt_y2))
			if iou >= 0.5:
				found_match = True
				gt_box['bbox_matched'] = True
				break
			else:
				continue

		T[pred_class].append(int(found_match))

	for gt_box in gt:
		if not gt_box['bbox_matched'] and not gt_box['difficult']:
			if gt_box['class'] not in P:
				P[gt_box['class']] = []
				T[gt_box['class']] = []

			T[gt_box['class']].append(1)
			P[gt_box['class']].append(0)

	#import pdb
	#pdb.set_trace()
	return T, P

示例3

def get_map(pred, gt, f):
    T = {}
    P = {}
    fx, fy = f

    for bbox in gt:
        bbox['bbox_matched'] = False

    pred_probs = np.array([s['prob'] for s in pred])
    box_idx_sorted_by_prob = np.argsort(pred_probs)[::-1]

    for box_idx in box_idx_sorted_by_prob:
        pred_box = pred[box_idx]
        pred_class = pred_box['class']
        pred_x1 = pred_box['x1']
        pred_x2 = pred_box['x2']
        pred_y1 = pred_box['y1']
        pred_y2 = pred_box['y2']
        pred_prob = pred_box['prob']
        if pred_class not in P:
            P[pred_class] = []
            T[pred_class] = []
        P[pred_class].append(pred_prob)
        found_match = False

        for gt_box in gt:
            gt_class = gt_box['class']
            gt_x1 = gt_box['x1']/fx
            gt_x2 = gt_box['x2']/fx
            gt_y1 = gt_box['y1']/fy
            gt_y2 = gt_box['y2']/fy
            gt_seen = gt_box['bbox_matched']
            if gt_class != pred_class:
                continue
            if gt_seen:
                continue
            iou = data_generators.iou((pred_x1, pred_y1, pred_x2, pred_y2), (gt_x1, gt_y1, gt_x2, gt_y2))
            if iou >= 0.5:
                found_match = True
                gt_box['bbox_matched'] = True
                break
            else:
                continue

        T[pred_class].append(int(found_match))

    for gt_box in gt:
        if not gt_box['bbox_matched'] and not gt_box['difficult']:
            if gt_box['class'] not in P:
                P[gt_box['class']] = []
                T[gt_box['class']] = []

            T[gt_box['class']].append(1)
            P[gt_box['class']].append(0)

    #import pdb
    #pdb.set_trace()
    return T, P

示例4

def get_map(pred, gt, f):
	T = {}
	P = {}
	fx, fy = f

	for bbox in gt:
		bbox['bbox_matched'] = False

	pred_probs = np.array([s['prob'] for s in pred])
	box_idx_sorted_by_prob = np.argsort(pred_probs)[::-1]

	for box_idx in box_idx_sorted_by_prob:
		pred_box = pred[box_idx]
		pred_class = pred_box['class']
		pred_x1 = pred_box['x1']
		pred_x2 = pred_box['x2']
		pred_y1 = pred_box['y1']
		pred_y2 = pred_box['y2']
		pred_prob = pred_box['prob']
		if pred_class not in P:
			P[pred_class] = []
			T[pred_class] = []
		P[pred_class].append(pred_prob)
		found_match = False

		for gt_box in gt:
			gt_class = gt_box['class']
			gt_x1 = gt_box['x1']/fx
			gt_x2 = gt_box['x2']/fx
			gt_y1 = gt_box['y1']/fy
			gt_y2 = gt_box['y2']/fy
			gt_seen = gt_box['bbox_matched']
			if gt_class != pred_class:
				continue
			if gt_seen:
				continue
			iou = data_generators.iou((pred_x1, pred_y1, pred_x2, pred_y2), (gt_x1, gt_y1, gt_x2, gt_y2))
			if iou >= 0.5:
				found_match = True
				gt_box['bbox_matched'] = True
				break
			else:
				continue

		T[pred_class].append(int(found_match))

	for gt_box in gt:
		if not gt_box['bbox_matched'] and not gt_box['difficult']:
			if gt_box['class'] not in P:
				P[gt_box['class']] = []
				T[gt_box['class']] = []

			T[gt_box['class']].append(1)
			P[gt_box['class']].append(0)

	#import pdb
	#pdb.set_trace()
	return T, P

Python源码示例：keras.iou()

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