Adding support for multiple inputs, resolved output errors

app.py

@@ -81,7 +81,7 @@ def download_and_unzip_google_drive_file(file_id, output_path, unzip_path):
     
 
 # @spaces.GPU()
-def doo(video, fps, min_track_length, progress=gr.Progress()):
+def doo(video, tiff_stack, images, fps, min_track_length, progress=gr.Progress()):
     # download and unzip models
     # file_id = '1agsLD5HV_VmDNpDhjHXTCAVmGUm2IQ6p'
     # output_path = 'models.zip'
@@ -161,47 +161,91 @@ def doo(video, fps, min_track_length, progress=gr.Progress()):
         progress(2 / 3, desc=f"Tracking {2}/{3}")
         folder_path = analyse_tracking(video_num=video_num, min_track_length=min_track_length, data_feature_path=feature_data_path, data_root_path=final_data_dir, plot=True)
         progress(3 / 3, desc=f"Tracking {3}/{3}")
-        output_video = gen_tracking_video(video_num=video_num, fps=fps, data_path=feature_data_path)
-        final_video = os.path.basename(output_video)
-        shutil.copy(output_video, final_video)
-        print(output_video)
-        print(final_video)
+        output_video1 = gen_tracking_video(video_num=video_num, fps=fps, data_path=feature_data_path)
+        output_video2 = gen_tracking_video(video_num=video_num, fps=fps, data_path=feature_data_path, all_images=True)
+        final_videos = [os.path.basename(output_video1), os.path.basename(output_video2)]
+        shutil.copy(output_video1, final_videos[0])
+        shutil.copy(output_video2, final_videos[1])
+        print(output_video1)
+        print(final_videos)
         
         search_pattern = "TrackedRawData"
         tracking_preds = find_and_return_csv_files(folder_path, search_pattern)
          
  
-    return final_video, tracking_preds
+    return final_video[0], final_video[1], tracking_preds
 
 
-examples = [['RBS_2_4_h264.mp4'], ['RBS_4_4_h264.mp4']]# ['RBS_7_6_h264.mp4']]
 
-title = "🎞️ MEMTrack Bacteria Tracking Video Tool"
-description = "Upload a video or selct from example to track. <br><br> If the input video does not play on browser, ensure its in a browser accetable format. Output will be generated iirespective of playback on browser. Refer: https://colab.research.google.com/drive/1U5pX_9iaR_T8knVV7o4ftKdDoGndCdEM?usp=sharing"
 
+if __name__ == "__main__":
 
-inputs = [
-    gr.Video(label="Input Video"),
-    gr.Slider(minimum=1, maximum=100, step=1, default=60, label="FPS", choices=[10, 20, 30, 60]),
-    gr.Slider(minimum=1, maximum=1000, step=1, default=60, label="Minimum Track Length Threshold", choices=[5, 10, 20, 50, 100])
-]
+    examples = [['RBS_2_4_h264.mp4'], ['RBS_4_4_h264.mp4'], ['RBS_7_6_h264.mp4']]
+    
+    title = "🎞️ MEMTrack Bacteria Tracking Video Tool"
+    description = "Upload a video or selct from example to track. <br><br> If the input video does not play on browser, ensure its in a browser accetable format. Output will be generated iirespective of playback on browser. Refer: https://colab.research.google.com/drive/1U5pX_9iaR_T8knVV7o4ftKdDoGndCdEM?usp=sharing"
 
-outputs = [
-    gr.Video(label="Tracked Video"),
-    gr.Files(label="CSV Data")
-]
 
+    with gr.Blocks() as demo:
+        gr.Markdown(f"# {title}")
+        gr.Markdown(description)
+        
+        with gr.Row():
+            with gr.Column():
+                gr.Markdown("Select the appropriate tab to upload a video, a TIFF stack, or a folder containing image frames.")
+                
+                with gr.Tabs():
+                    with gr.Tab("Upload Video"):
+                        video_input = gr.Video(label="Video File")
+            
+                    with gr.Tab("Upload TIFF Stack"):
+                        tiff_input = gr.File(label="TIFF File", file_types=["tif", "tiff"])
+            
+                    with gr.Tab("Upload Images"):
+                        image_input = gr.File(label="Image Files", file_types=["jpg", "jpeg", "png", "tif", "tiff"], file_count="multiple")
+        
+                # Common sliders for all inputs
+                fps_slider = gr.Slider(minimum=1, maximum=100, step=1, value=60, label="Output Video FPS")
+                track_length_slider = gr.Slider(minimum=0, maximum=1000, step=1, value=60, label="Minimum Track Length Threshold")
+            with gr.Column():
+                    outputs = [
+                        gr.Video(label="Tracked Video (tracked frames)"),
+                        gr.Video(label="Tracked Video (all frames)"),
+                        gr.Files(label="CSV Data")
+                    ]
+            
+    
+        submit_button = gr.Button("Process Input")
+        submit_button.click(
+            fn=doo,
+            inputs=[video_input, tiff_input, image_input, fps_slider, track_length_slider],
+            outputs=outputs
+        )
+    
+    demo.launch(share=True, debug=True)        
 
-iface = gr.Interface(
-    fn=doo,
-    inputs=inputs,
-    outputs=outputs,
-    examples=examples,
-    title=title,
-    description=description,
-    cache_examples=True, 
-)
 
 
-if __name__ == "__main__":
-    iface.launch(share=True)
+    
+
+
+
+# inputs = [
+#     gr.Video(label="Input Video"),
+#     gr.Slider(minimum=1, maximum=100, step=1, value=60, label="Output Video FPS" ),
+#     gr.Slider(minimum=0, maximum=1000, step=1, value=60, label="Minimum Track Length Threshold")
+# ]
+
+
+# iface = gr.Interface(
+#     fn=doo,
+#     inputs=inputs,
+#     outputs=outputs,
+#     examples=examples,
+#     title=title,
+#     description=description,
+#     cache_examples=False, 
+# )
+
+# if __name__ == "__main__":
+#     iface.launch(share=True, debug=True)