Implement orphaned temporary folder re-import and resume feature with web UI modal

2026-06-30 15:49:19 -04:00
parent 2d1fa83d58
commit f523a393cb
3 changed files with 275 additions and 1 deletions
@@ -1590,8 +1590,102 @@ def cleanup_temp(req: CleanupTempRequest):
        except Exception as e:
            errors.append(f"Error removing {path}: {str(e)}")
            
+class ReimportTempRequest(BaseModel):
+    video_path: str
+    model: str = "realesrgan-x4plus"
+    scale: int = 4
+    tile_size: int = 256
+    preserve_audio: bool = True
+    ai_face_restoration: bool = False
+    ai_rife_interpolation: bool = False
+    ai_audio_denoise: bool = False
+    ss: str | None = None
+    t: str | None = None
+    gpu_ids: str | None = None
+    tta: bool = False
+    unsharp: bool = False
+    double_fps: bool = False
+    preserve_subtitles: bool = True
+    start_sec: float | None = None
+    end_sec: float | None = None
+    crf: int = 18
+    preset: str = "medium"
+    denoise: bool = False
+    sharpen: bool = False
+    interpolation: bool = False
+    transcode_format: str = "mp4"
+    temp_dir: str | None = None
+
+@app.post("/api/system/temp-reimport/{job_id}")
+def reimport_temp(job_id: str, req: ReimportTempRequest):
+    if job_id in jobs_db:
+        raise HTTPException(status_code=400, detail="Job already exists in database.")
+    
+    # Verify the video path is valid
+    if not os.path.exists(req.video_path):
+        raise HTTPException(status_code=400, detail=f"Video file not found at: {req.video_path}")
+        
+    # Reconstruct the job dictionary
+    job_dict = {
+        "job_id": job_id,
+        "video_path": req.video_path,
+        "model": req.model,
+        "scale": req.scale,
+        "tile_size": req.tile_size,
+        "preserve_audio": req.preserve_audio,
+        "ai_face_restoration": req.ai_face_restoration,
+        "ai_rife_interpolation": req.ai_rife_interpolation,
+        "ai_audio_denoise": req.ai_audio_denoise,
+        "ss": req.ss,
+        "t": req.t,
+        "gpu_ids": req.gpu_ids,
+        "tta": req.tta,
+        "unsharp": req.unsharp,
+        "double_fps": req.double_fps,
+        "preserve_subtitles": req.preserve_subtitles,
+        "start_sec": req.start_sec,
+        "end_sec": req.end_sec,
+        "crf": req.crf,
+        "preset": req.preset,
+        "denoise": req.denoise,
+        "sharpen": req.sharpen,
+        "interpolation": req.interpolation,
+        "transcode_format": req.transcode_format,
+        "temp_dir": req.temp_dir,
+        "status": "paused",  # Start as paused so it can be resumed
+        "progress": 0.0,
+        "current_frame": 0,
+        "total_frames": 0,
+        "eta": "Ready to resume"
+    }
+    
+    job = upscaler.UpscaleJob.from_dict(job_dict)
+    
+    # Calculate progress based on existing frames in the temp directory if possible
+    job_temp_dir = os.path.join(req.temp_dir if req.temp_dir else upscaler.TEMP_DIR, job_id)
+    input_frames_dir = os.path.join(job_temp_dir, "input_frames")
+    output_frames_dir = os.path.join(job_temp_dir, "output_frames")
+    
+    total_frames = 0
+    if os.path.exists(input_frames_dir):
+        total_frames = len([f for f in os.listdir(input_frames_dir) if f.startswith("frame_")])
+        job.total_frames = total_frames
+        
+    if os.path.exists(output_frames_dir):
+        out_frames = len([f for f in os.listdir(output_frames_dir) if f.startswith("frame_")])
+        job.current_frame = out_frames
+        if total_frames > 0:
+            job.progress = min(99.0, round((out_frames / total_frames) * 100.0, 2))
+            
+    jobs_db[job_id] = job
    save_jobs_db()
-    return {"cleaned": cleaned, "errors": errors}
+    
+    # Auto-resume the job by adding it to the queue
+    job_queue.put(job_id)
+    job.update_status("queued", eta="Queued for resume...")
+    save_jobs_db()
+    
+    return {"status": "success", "job_id": job_id}

 # ─── Distributed Processing Coordinator & Worker Endpoints ────────────────