Update app.py

app.py

@@ -16,9 +16,13 @@ import random
 import gc
 from optimization import optimize_pipeline_
 
+import ffmpeg
+import tempfile
+import os
+
 
 MODEL_ID = "Wan-AI/Wan2.2-T2V-A14B-Diffusers"
-HF_MODEL = os.environ.get("HF_UPLOAD_REPO", "rahul7star/VideoExplain")
+
 
 LANDSCAPE_WIDTH = 832
 LANDSCAPE_HEIGHT = 480
@@ -73,8 +77,81 @@ import uuid
 import logging
 from datetime import datetime
 from huggingface_hub import HfApi, upload_file
+import tempfile
+import random
+import logging
+from datetime import datetime
+import uuid
+import numpy as np
+import torch
+import ffmpeg
 
-def upload_to_hf(video_path, summary_text):
+HF_MODEL = os.environ.get("HF_UPLOAD_REPO", "rahul7star/VideoExplain")
+def upload_to_hf(video_path: str, summary_text: str):
+    api = HfApi()
+    # Create date-based folder
+    today_str = datetime.now().strftime("%Y-%m-%d")
+    unique_subfolder = f"WANT2V-EXP-upload_{uuid.uuid4().hex[:8]}"
+    hf_folder = f"{today_str}/{unique_subfolder}"
+    logging.info(f"Uploading to HF folder: {hf_folder}")
+
+    # Upload video
+    video_filename = os.path.basename(video_path)
+    video_hf_path = f"{hf_folder}/{video_filename}"
+    upload_file(
+        path_or_fileobj=video_path,
+        path_in_repo=video_hf_path,
+        repo_id=HF_MODEL,
+        repo_type="model",
+        token=os.environ.get("HUGGINGFACE_HUB_TOKEN"),
+    )
+    logging.info(f"✅ Uploaded video: {video_hf_path}")
+
+    # Upload summary
+    summary_file = os.path.join(tempfile.gettempdir(), "summary.txt")
+    with open(summary_file, "w", encoding="utf-8") as f:
+        f.write(summary_text)
+
+    summary_hf_path = f"{hf_folder}/summary.txt"
+    upload_file(
+        path_or_fileobj=summary_file,
+        path_in_repo=summary_hf_path,
+        repo_id=HF_MODEL,
+        repo_type="model",
+        token=os.environ.get("HUGGINGFACE_HUB_TOKEN"),
+    )
+    logging.info(f"✅ Uploaded summary: {summary_hf_path}")
+
+    return hf_folder
+
+
+def save_video_ffmpeg(frames: list, video_path: str, fps: int = FIXED_FPS):
+    h, w, c = frames[0].shape
+    process = (
+        ffmpeg
+        .input(
+            'pipe:', format='rawvideo', pix_fmt='rgb24',
+            s=f'{w}x{h}', framerate=fps
+        )
+        .output(
+            video_path,
+            pix_fmt='yuv420p',
+            vcodec='libx264',
+            crf=18,
+            preset='slow'
+        )
+        .overwrite_output()
+        .run_async(pipe_stdin=True)
+    )
+    for frame in frames:
+        process.stdin.write(frame.astype(np.uint8).tobytes())
+    process.stdin.close()
+    process.wait()
+    logging.info(f"✅ Video saved to {video_path}")
+
+
+
+def upload_to_hf0(video_path, summary_text):
     api = HfApi()
     
     # Create a date-based folder (YYYY-MM-DD)
@@ -130,7 +207,6 @@ def get_duration(
     return steps * 15
 
 @spaces.GPU(duration=get_duration)
-
 def generate_video(
     prompt,
     negative_prompt=default_negative_prompt,
@@ -161,15 +237,13 @@ def generate_video(
     ).frames[0]
 
   
-    video_path_raw = os.path.join(tempfile.gettempdir(), f"video_raw_{uuid.uuid4().hex[:8]}.mp4")
-    export_to_video(output_frames_list, video_path_raw, fps=FIXED_FPS)
+  
+    video_path = os.path.join(tempfile.gettempdir(), f"video_{current_seed}.mp4")
+    save_video_ffmpeg(output_frames_list, video_path, fps=FIXED_FPS)
 
    
-    video_path = os.path.join(tempfile.gettempdir(), f"video_{uuid.uuid4().hex[:8]}.mp4")
-    improve_video_quality(video_path_raw, video_path, bitrate="8M")
-
-    
-    hf_folder = upload_to_hf(video_path, prompt)
+    hf_folder = upload_to_hf(video_path, summary_text=prompt)
+    logging.info(f"✅ Uploaded folder: {hf_folder}")
 
     return video_path, current_seed