norm = norm * 0.1
# 均值加 0.5，保证大部分的梯度值为正
norm = norm + 0.5
# 把 0，1 以外的梯度值分别设置为 0 和 1
norm = norm.clip(0, 1)
return norm
if __name__ == '__main__':
ssd = SSD()
model = get_ssd("train", 3) # ssd.net
model.load_state_dict(
torch.load(
"F:/Iris_SSD_small/ssd-pytorch-master/logs/Epoch50-Loc0.0260-Conf0.1510.pth",
map_location=torch.device('cuda')))
ssd.net = model.eval()
ssd.net = torch.nn.DataParallel(ssd.net)
# ssd.net = ssd.net.cpu() # ****
# criterion = MultiBoxLoss(3, 0.5, True, 0, True, 3, 0.5,False, True)
model = ssd.net.module
imgPath = '1.bmp'
image = Image.open(imgPath)
image.show()
image_size = image.size
image = image.convert('RGB')
# r_image = ssd.detect_image(image)
# r_image.show()
# -------------------------------------------- #
norm = norm * 0.1
# 均值加 0.5，保证大部分的梯度值为正
norm = norm + 0.5
# 把 0，1 以外的梯度值分别设置为 0 和 1
norm = norm.clip(0, 1)
return norm
if __name__ == '__main__':
ssd = SSD()
model = get_ssd("train", 3) # ssd.net
model.load_state_dict(
torch.load(
"F:/Iris_SSD_small/ssd-pytorch-master/logs/Epoch50-Loc0.0260-Conf0.1510.pth",
map_location=torch.device('cuda')))
ssd.net = model.eval()
ssd.net = torch.nn.DataParallel(ssd.net)
ssd.net = ssd.net.cpu() # ****
# criterion = MultiBoxLoss(3, 0.5, True, 0, True, 3, 0.5,False, True)
model = ssd.net.module
imgPath = '1.bmp'
image = Image.open(imgPath)
image.show()
image = image.convert('RGB')
# r_image = ssd.detect_image(image)
# r_image.show()
# -------------------------------------------- #
