Add slider view and cache examples

app.py

@@ -8,6 +8,7 @@ import torch
 import torch.nn.functional as F
 from torchvision.transforms import Compose
 import tempfile
+from gradio_imageslider import ImageSlider
 
 from depth_anything.dpt import DPT_DINOv2
 from depth_anything.util.transform import Resize, NormalizeImage, PrepareForNet
@@ -58,11 +59,13 @@ with gr.Blocks(css=css) as demo:
 
     with gr.Row():
         input_image = gr.Image(label="Input Image", type='numpy', elem_id='img-display-input')
-        depth_image = gr.Image(label="Depth Map", elem_id='img-display-output')
+        depth_image_slider = ImageSlider(label="Depth Map with Slider View", elem_id='img-display-output', position=0)
     raw_file = gr.File(label="16-bit raw depth (can be considered as disparity)")
     submit = gr.Button("Submit")
 
     def on_submit(image):
+        original_image = image.copy()
+
         h, w = image.shape[:2]
 
         image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) / 255.0
@@ -80,16 +83,16 @@ with gr.Blocks(css=css) as demo:
         depth = depth.cpu().numpy().astype(np.uint8)
         colored_depth = cv2.applyColorMap(depth, cv2.COLORMAP_INFERNO)[:, :, ::-1]
 
-        return [colored_depth, tmp.name]
+        return [(original_image, colored_depth), tmp.name]
+
+    submit.click(on_submit, inputs=[input_image], outputs=[depth_image_slider, raw_file])
 
-    submit.click(on_submit, inputs=[input_image], outputs=[depth_image, raw_file])
-    
     example_files = os.listdir('examples')
     example_files.sort()
     example_files = [os.path.join('examples', filename) for filename in example_files]
-    examples = gr.Examples(examples=example_files, inputs=[input_image])
+    examples = gr.Examples(examples=example_files, inputs=[input_image], outputs=[depth_image_slider, raw_file], fn=on_submit, cache_examples=True)
 
 
 if __name__ == '__main__':
     demo.queue().launch()
-    
+

requirements.txt

@@ -1,3 +1,4 @@
+gradio_imageslider
 torch
 torchvision
-opencv-python
+opencv-python