Update app.py

app.py

@@ -33,8 +33,9 @@ def get_video_dimension(filepath):
     video = cv2.VideoCapture(filepath)
     width = int(video.get(cv2.CAP_PROP_FRAME_WIDTH))
     height = int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
+    fps = int(video.get(cv2.CAP_PROP_FPS))
     video.release()
-    return width, height
+    return width, height, fps
 
 def resize_video(input_path, output_path, width):
     # Load the video clip
@@ -59,9 +60,9 @@ def run_inference(prompt, video_path, condition, video_length):
 
     # Call the function to resize the video
     video_path = resize_video(input_vid, resized_vid, width=512)
-    width, height = get_video_dimension(video_path)
+    width, height, fps = get_video_dimension(video_path)
 
-    print(f"{width} x {height}")
+    print(f"{width} x {height} | {fps}")
     
     output_path = 'output/'
     os.makedirs(output_path, exist_ok=True)
@@ -75,9 +76,9 @@ def run_inference(prompt, video_path, condition, video_length):
         os.remove(video_path_output)
 
     if video_length > 12:
-        command = f"python inference.py --prompt '{prompt}' --condition '{condition}' --video_path '{video_path}' --output_path '{output_path}' --width {width} --height {height} --video_length {video_length} --is_long_video"
+        command = f"python inference.py --prompt '{prompt}' --condition '{condition}' --video_path '{video_path}' --output_path '{output_path}' --width {width} --height {height} --fps {fps} --video_length {video_length} --is_long_video"
     else:
-        command = f"python inference.py --prompt '{prompt}' --condition '{condition}' --video_path '{video_path}' --output_path '{output_path}' --width {width} --height {height} --video_length {video_length}"
+        command = f"python inference.py --prompt '{prompt}' --condition '{condition}' --video_path '{video_path}' --output_path '{output_path}' --width {width} --height {height} --fps {fps} --video_length {video_length}"
     subprocess.run(command, shell=True)
 
     # Construct the video path
@@ -87,13 +88,18 @@ def run_inference(prompt, video_path, condition, video_length):
 
     return "done", video_path_output 
 
-
-with gr.Blocks() as demo:
-    with gr.Column():
+css="""
+#col-container {max-width: 510px; margin-left: auto; margin-right: auto;}
+"""
+with gr.Blocks(css=css) as demo:
+    with gr.Column(col-container):
+        gr.Markdown("""
+            <h1 style="text-align: center;">ControlVideo</h1>
+        """)
         prompt = gr.Textbox(label="prompt")
         video_path = gr.Video(source="upload", type="filepath")
-        condition = gr.Textbox(label="Condition", value="depth")
-        video_length = gr.Slider(label="video length", minimum=1, maximum=15, step=1, value=2)
+        condition = gr.Dropdown(label="Condition", choices=["depth", "canny", "pose"], value="depth")
+        video_length = gr.Slider(label="Video length", info="How many frames do you want to process ?", minimum=1, maximum=12, step=1, value=2)
         #seed = gr.Number(label="seed", value=42)
         submit_btn = gr.Button("Submit")
         video_res = gr.Video(label="result")