add data/

app.py

@@ -31,7 +31,7 @@ def lowlight(image_path):
 	data_lowlight = data_lowlight.cpu().unsqueeze(0)
 
 	DCE_net = model.enhance_net_nopool().cpu()
-	DCE_net.load_state_dict(torch.load('Epoch99.pth'))
+	DCE_net.load_state_dict(torch.load('snapshots/Epoch99.pth'))
 	start = time.time()
 	_,enhanced_image,_ = DCE_net(data_lowlight)
 
@@ -47,8 +47,13 @@ def lowlight(image_path):
 if __name__ == '__main__':
 # test_images
 	with torch.no_grad():
+		filePath = 'data/test_data/'
+	
+		file_list = os.listdir(filePath)
 
-			for image
+		for file_name in file_list:
+			test_list = glob.glob(filePath+file_name+"/*") 
+			for image in test_list:
 				# image = image
 				print(image)
 				lowlight(image)
@@ -58,7 +63,7 @@ title = "Compound Multi-branch Feature Fusion for Image Restoration (Deblur)"
 description = "Gradio demo for CMFNet. CMFNet achieves competitive performance on three tasks: image deblurring, image dehazing and image deraindrop. Here, we provide a demo for image deblur. To use it, simply upload your image, or click one of the examples to load them. Reference from: https://huggingface.co/akhaliq"
 article = "<p style='text-align: center'><a href='https://' target='_blank'>Compound Multi-branch Feature Fusion for Real Image Restoration</a> | <a href='https://github.com/FanChiMao/CMFNet' target='_blank'>Github Repo</a></p> <center><img src='https://visitor-badge.glitch.me/badge?page_id=52Hz_CMFNet_deblurring' alt='visitor badge'></center>"
 
-examples = [['01.jpg'], ['02.jpg'],]
+examples = [['data/test_data//01.jpg'], ['data/test_data//02.jpg'], ['data/test_data//03.jpg'],]
 gr.Interface(
     inference,
     [gr.inputs.Image(type="pil", label="Input")],