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fix bugs at examples/yolov3.py (#11614)

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* Update load_weight. Give valid model url

* Fix bug in iou function
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Sardor 2025-08-12 10:14:47 +09:00 • committed by GitHub
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1 changed files with 9 additions and 9 deletions
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18
examples/yolov3.py
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@ -71,8 +71,8 @@ def bbox_iou(box1, box2):
# get the coordinates of the intersection rectangle
inter_rect_x1 = np.maximum(b1_x1, b2_x1)
inter_rect_y1 = np.maximum(b1_y1, b2_y1)
inter_rect_x2 = np.maximum(b1_x2, b2_x2)
inter_rect_y2 = np.maximum(b1_y2, b2_y2)
inter_rect_x2 = np.minimum(b1_x2, b2_x2)
inter_rect_y2 = np.minimum(b1_y2, b2_y2)
#Intersection area
inter_area = np.clip(inter_rect_x2 - inter_rect_x1 + 1, 0, 99999) * np.clip(inter_rect_y2 - inter_rect_y1 + 1, 0, 99999)
#Union Area
@ -297,13 +297,13 @@ class Darknet:
# Get the number of weights of batchnorm
num_bn_biases = math.prod(bn.bias.shape)
# Load weights
bn_biases = Tensor(weights[ptr:ptr + num_bn_biases])
bn_biases = Tensor(weights[ptr:ptr + num_bn_biases].astype(np.float32))
ptr += num_bn_biases
bn_weights = Tensor(weights[ptr:ptr+num_bn_biases])
bn_weights = Tensor(weights[ptr:ptr+num_bn_biases].astype(np.float32))
ptr += num_bn_biases
bn_running_mean = Tensor(weights[ptr:ptr+num_bn_biases])
bn_running_mean = Tensor(weights[ptr:ptr+num_bn_biases].astype(np.float32))
ptr += num_bn_biases
bn_running_var = Tensor(weights[ptr:ptr+num_bn_biases])
bn_running_var = Tensor(weights[ptr:ptr+num_bn_biases].astype(np.float32))
ptr += num_bn_biases
# Cast the loaded weights into dims of model weights
bn_biases = bn_biases.reshape(shape=tuple(bn.bias.shape))
@ -319,7 +319,7 @@ class Darknet:
# load biases of the conv layer
num_biases = math.prod(conv.bias.shape)
# Load weights
conv_biases = Tensor(weights[ptr: ptr+num_biases])
conv_biases = Tensor(weights[ptr: ptr+num_biases].astype(np.float32))
ptr += num_biases
# Reshape
conv_biases = conv_biases.reshape(shape=tuple(conv.bias.shape))
@ -327,7 +327,7 @@ class Darknet:
conv.bias = conv_biases
# Load weighys for conv layers
num_weights = math.prod(conv.weight.shape)
conv_weights = Tensor(weights[ptr:ptr+num_weights])
conv_weights = Tensor(weights[ptr:ptr+num_weights].astype(np.float32))
ptr += num_weights
conv_weights = conv_weights.reshape(shape=tuple(conv.weight.shape))
conv.weight = conv_weights
@ -371,7 +371,7 @@ class Darknet:
if __name__ == "__main__":
model = Darknet(fetch('https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/yolov3.cfg').read_bytes())
print("Loading weights file (237MB). This might take a while…")
model.load_weights('https://pjreddie.com/media/files/yolov3.weights')
model.load_weights('https://github.com/shadiakiki1986/yolov3.weights/releases/download/3.0.1/yolov3.weights')
if len(sys.argv) > 1:
url = sys.argv[1]
else: