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() # -------------------------------------------- #