Create video_enhancer.py

app.py

@@ -1,11 +1,13 @@
 from fastapi import FastAPI, File, UploadFile, HTTPException
 from fastapi.responses import StreamingResponse
 from ./image_enhancer import EnhancementMethod, Enhancer
+from vidoe_enhancer import VideoEnhancer
 from pydantic import BaseModel
 from PIL import Image
 from io import BytesIO
 import base64
 import numpy as np
+import magic
 
 class EnhancementRequest(BaseModel):
     method: EnhancementMethod = EnhancementMethod.gfpgan
@@ -23,7 +25,7 @@ app = FastAPI()
 def greet_json():
     return {"Initializing GlamApp Enhancer"}
 
-@app.post("/enhance")
+@app.post("/enhance/image/")
 async def enhance_image(
     file: UploadFile = File(...),
     request: EnhancementRequest = EnhancementRequest()
@@ -48,4 +50,25 @@ async def enhance_image(
         return StreamingResponse(img_byte_arr, media_type="image/png")
 
     except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
+        raise HTTPException(status_code=500, detail=str(e))
+        
+@app.post("/enhance/video/")
+async def enhance_video(file: UploadFile = File(...)):
+    enhancer = VideoEnhancer()
+    file_header = await file.read(1024)
+    file.file.seek(0)
+    mime = magic.Magic(mime=True)
+    file_mime_type = mime.from_buffer(file_header)
+    
+    accepted_mime_types = [
+        'video/mp4',
+        'video/mpeg',
+        'video/x-msvideo',
+        'video/quicktime',
+        'video/x-matroska',
+        'video/webm'
+    ]
+    
+    if file_mime_type not in accepted_mime_types:
+        raise HTTPException(status_code=400, detail="Invalid file type. Please upload a video file.")
+    return await enhancer.stream_enhanced_video(file)

video_enhancer.py

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