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4a8a636
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Create video_enhancer.py

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  1. video_enhancer.py +68 -0
video_enhancer.py ADDED
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+ import cv2
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+ import numpy as np
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+ import torch
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+ import io
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+ import asyncio
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+ from basicsr.archs.rrdbnet_arch import RRDBNet
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+ from realesrgan import RealESRGANer
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+ from huggingface_hub import hf_hub_download
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+ from concurrent.futures import ThreadPoolExecutor
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+
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+ class VideoEnhancer:
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+ def __init__(self, model_name="RealESRGAN_x4plus"):
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+ self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
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+ self.model = self.load_model(model_name)
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+ self.executor = ThreadPoolExecutor(max_workers=4)
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+
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+ def load_model(self, model_name):
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+ if model_name == "RealESRGAN_x4plus":
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+ model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4)
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+ model_path = hf_hub_download("schwgHao/RealESRGAN_x4plus", "RealESRGAN_x4plus.pth")
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+ return RealESRGANer(scale=4, model_path=model_path, model=model, tile=0, tile_pad=10, pre_pad=0, half=True)
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+ else:
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+ raise ValueError(f"Unsupported model: {model_name}")
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+
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+ async def enhance_frame(self, frame):
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+ loop = asyncio.get_running_loop()
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+
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+ frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
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+
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+ enhanced, _ = await loop.run_in_executor(self.executor, self.model.enhance, frame_rgb)
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+
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+ return cv2.cvtColor(enhanced, cv2.COLOR_RGB2BGR)
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+
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+ async def process_video(self, input_bytes, output_bytes):
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+ cap = cv2.VideoCapture(input_bytes)
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+ width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
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+ height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
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+ fps = cap.get(cv2.CAP_PROP_FPS)
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+
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+ fourcc = cv2.VideoWriter_fourcc(*'mp4v')
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+ out = cv2.VideoWriter(output_bytes, fourcc, fps, (width * 4, height * 4))
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+
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+ while cap.isOpened():
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+ ret, frame = cap.read()
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+ if not ret:
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+ break
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+ enhanced_frame = await self.enhance_frame(frame)
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+ out.write(enhanced_frame)
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+
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+ cap.release()
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+ out.release()
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+
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+ async def stream_enhanced_video(self, video_file):
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+ video_bytes = await video_file.read()
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+ cap = cv2.VideoCapture(io.BytesIO(video_bytes).getvalue())
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+
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+ async def generate():
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+ while cap.isOpened():
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+ ret, frame = cap.read()
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+ if not ret:
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+ break
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+ enhanced_frame = await self.enhance_frame(frame)
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+ _, buffer = cv2.imencode('.jpg', enhanced_frame)
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+ yield (b'--frame\r\n'
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+ b'Content-Type: image/jpeg\r\n\r\n' + buffer.tobytes() + b'\r\n')
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+ cap.release()
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+
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+ return StreamingResponse(generate(), media_type="multipart/x-mixed-replace; boundary=frame")