ValueError: cannot reshape array of size 692224 into shape (1,3,416,416)-yolov5 cpu error - resize

Question

I was trying to run my yolov5 custom model on cpu and I got this error.
this is the github page I have used : https://github.com/Amelia0911/onnxruntime-for-yolov5
import onnxruntime
from models.utils import *
import time
IMAGE_SIZE = (416, 416)
CONF_TH = 0.3
NMS_TH = 0.45
CLASSES = 80
model = onnxruntime.InferenceSession("models_train/bestnone.onnx")
anchor_list = [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]]
stride = [8, 16, 32]
def draw(img, boxinfo, dst, id):
for *xyxy, conf, cls in boxinfo:
label = '{}|{}'.format(int(cls), '%.2f' % conf)
plot_one_box(xyxy, img, label=label, color=[0, 0, 255])
cv2.imencode('.jpg', img)[1].tofile(dst)
def detect(image):
img = cv2.resize(image,IMAGE_SIZE)
img = img.transpose(2, 0, 1)
dataset = (img, image)
img = dataset[0].astype('float32')
img_size = [dataset[0].shape[1], dataset[0].shape[2]]
img /= 255.0
img = img.reshape(1, 3, img_size[0], img_size[1])
inputs = {model.get_inputs()[0].name: img}
pred = torch.tensor(model.run(None, inputs)[0])
anchor = torch.tensor(anchor_list).float().view(3, -1, 2)
area = img_size[0]*img_size[1]
size = [int(area/stride[0]**2), int(area/stride[1]**2), int(area/stride[2]**2)]
feature = [[int(j/stride[i]) for j in img_size] for i in range(3)]
y = []
y.append(pred[:, :size[0]*3, :])
y.append(pred[:, size[0]*3:size[0]*3+size[1]*3, :])
y.append(pred[:, size[0]*3+size[1]*3:, :])
grid = []
for k, f in enumerate(feature):
grid.append([[i, j] for j in range(f[0]) for i in range(f[1])])
z = []
for i in range(3):
src = y[i]
xy = src[..., 0:2] * 2. - 0.5
wh = (src[..., 2:4] * 2) ** 2
dst_xy = []
dst_wh = []
for j in range(3):
dst_xy.append((xy[:, j*size[i]:(j+1)*size[i], :] + torch.tensor(grid[i])) * stride[i])
dst_wh.append(wh[:, j*size[i]:(j+1)*size[i], :] * anchor[i][j])
src[..., 0:2] = torch.from_numpy(np.concatenate((dst_xy[0], dst_xy[1], dst_xy[2]), axis=1))
src[..., 2:4] = torch.from_numpy(np.concatenate((dst_wh[0], dst_wh[1], dst_wh[2]), axis=1))
z.append(src.view(1, -1, CLASSES+5)) #85
pred = torch.cat(z, 1)
pred = nms(pred, CONF_TH, NMS_TH)
for det in pred:
if det is not None and len(det):
det[:, :4] = scale_coords(img.shape[2:], det[:, :4], dataset[1].shape).round()
if det == None:
return np.array([])
return det
if __name__ == '__main__':
import time
src = 'Temp-640x640.jpg'
t1 = time.time()
img = cv2.imdecode(np.fromfile(src, dtype=np.uint8), -1)
print(IMAGE_SIZE)
results = detect(img)
t2 = time.time()
print(results)
print("onnxruntime time = ", t2 - t1)
if results is not None and len(results):
draw(img, results, 'dst3.jpg', str(id))
print('Down!')
when I run this code I got the following error:
File "C:\Users\acer\.spyder-py3\metallic surface defect detection\3_onnx_cpu_detec.py", line 85, in <module>
results = detect(img)
File "C:\Users\acer\.spyder-py3\metallic surface defect detection\3_onnx_cpu_detec.py", line 30, in detect
img = img.reshape(1, 3, img_size[0], img_size[1])
ValueError: cannot reshape array of size 692224 into shape (1,3,416,416)
I think it is a color channel issue. I have tried to fix it .But it doesn't work .If someone know how to fix it please inform me.Thanks in advance