Update app.py

app.py

@@ -106,7 +106,7 @@ def process_brightness(
 
     return output_image
 
-def infer(video_in, prompt,
+def infer(video_in, trim_value, prompt,
                     negative_prompt,
                     conditioning_image,
                     num_inference_steps=30,
@@ -119,8 +119,8 @@ def infer(video_in, prompt,
     break_vid = get_frames(video_in)
     frames_list= break_vid[0]
     fps = break_vid[1]
-    #n_frame = int(trim_value*fps)
-    n_frame = len(frames_list)
+    n_frame = int(trim_value*fps)
+    #n_frame = len(frames_list)
     
     if n_frame >= len(frames_list):
         print("video is shorter than the cut value")
@@ -178,6 +178,7 @@ with gr.Blocks() as demo:
                 source="upload",
                 type="filepath"     
             )
+            trim_in = gr.Slider(label="Cut video at (s)", minimun=1, maximum=5, step=1, value=1)
             with gr.Accordion('Advanced options', open=False):
                 with gr.Row():
                     num_inference_steps = gr.Slider(
@@ -218,26 +219,11 @@ with gr.Blocks() as demo:
     submit_btn.click(
         fn=infer,
         inputs=[
-            video_in, prompt, negative_prompt, conditioning_image, num_inference_steps, size, guidance_scale, seed
+            video_in, prompt, trim_in, negative_prompt, conditioning_image, num_inference_steps, size, guidance_scale, seed
         ],
         outputs=output
     )
-    gr.Examples(
-        examples=[
-            ["a village in the mountains", "monochrome", "./conditioning_images/conditioning_image_1.jpg"],
-            ["three people walking in an alleyway with hats and pants", "monochrome", "./conditioning_images/conditioning_image_2.jpg"],
-            ["an anime character, natural skin", "monochrome, blue skin, grayscale", "./conditioning_images/conditioning_image_3.jpg"],
-            ["a man in a black suit", "monochrome", "./conditioning_images/conditioning_image_4.jpg"],
-            ["the forbidden city in beijing at sunset with a reflection in the water", "monochrome", "./conditioning_images/conditioning_image_5.jpg"],
-            ["a man in a white shirt holding his hand out in front of", "monochrome", "./conditioning_images/conditioning_image_6.jpg"],
-        ],
-        inputs=[
-            prompt, negative_prompt, conditioning_image
-        ],
-        outputs=output,
-        fn=infer,
-        cache_examples=False,
-    )
+    
     gr.Markdown(
         """
     * [Dataset](https://huggingface.co/datasets/ioclab/grayscale_image_aesthetic_3M)