add video upload

app.py

@@ -5,6 +5,7 @@ import os
 import cv2
 import math
 import json
+import time
 import subprocess
 import matplotlib
 matplotlib.use('Agg')
@@ -36,7 +37,7 @@ os.makedirs(os.path.join(os.getcwd(), 'clips'), exist_ok=True)
 
 current_model = 'nextjump_speed'
 onnx_file = hf_hub_download(repo_id="lumos-motion/nextjump", filename=f"{current_model}.onnx", repo_type="model", token=os.environ['DATASET_SECRET'])
-
+api = HfApi()
 
 if torch.cuda.is_available():
     print("Using CUDA")
@@ -236,6 +237,18 @@ def detect_relay_beeps(video_path, event_start, relay_length=30, n_jumpers=4, be
     return starts, ends
 
 
+def upload_video(out_text, in_video):
+    if out_text != '':
+        # generate a timestamp name for the video
+        upload_path = f"{int(time.time())}.mp4"
+        api.upload_file(
+            path_or_fileobj=in_video,
+            path_in_repo=upload_path,
+            repo_id="dylanplummer/single-rope-contest",
+            repo_type="dataset",
+        )
+
+
 def inference(in_video, use_60fps, model_choice, beep_detection_on, event_length, relay_detection_on, relay_length, switch_delay,
               count_only_api, api_key, seq_len=64, stride_length=32, stride_pad=3, batch_size=4,
               miss_threshold=0.8, marks_threshold=0.5, median_pred_filter=True, both_feet=True, 
@@ -262,6 +275,7 @@ def inference(in_video, use_60fps, model_choice, beep_detection_on, event_length
         ort_sess.run(None, {'video': np.zeros((4, 64, 3, IMG_SIZE, IMG_SIZE), dtype=np.float32)})
 
     in_video = download_clips(in_video, os.path.join(os.getcwd(), 'clips'), '00:00:00', '', use_60fps=use_60fps)
+    
     progress(0, desc="Running inference...")
     has_access = False
     if api_call:
@@ -796,7 +810,7 @@ with gr.Blocks() as demo:
     demo_inference = partial(inference, count_only_api=False, api_key=None)
     
     run_button.click(demo_inference, [in_video, use_60fps, model_choice, beep_detection_on, event_length, relay_detection_on, relay_length, switch_delay], 
-                     outputs=[out_text, out_plot, out_phase_spiral, out_phase, out_hist, out_event_type_dist])
+                     outputs=[out_text, out_plot, out_phase_spiral, out_phase, out_hist, out_event_type_dist]).then(upload_video, inputs=[out_text, in_video])
     api_inference = partial(inference, api_call=True)
     api_dummy_button.click(api_inference, [in_video, use_60fps, model_choice, beep_detection_on, event_length, relay_detection_on, relay_length, switch_delay, count_only, api_token], 
                            outputs=[period_length], api_name='inference')
@@ -810,6 +824,8 @@ with gr.Blocks() as demo:
                 inputs=[in_video, use_60fps, model_choice, beep_detection_on, event_length, relay_detection_on, relay_length, switch_delay], 
                 outputs=[out_text, out_plot, out_phase_spiral, out_phase, out_hist, out_event_type_dist],
                 fn=demo_inference, cache_examples=False)
+    
+
 
 
 if __name__ == "__main__":