Update gradio.py

gradio.py

@@ -1,4 +1,4 @@
-import sys
+'''import sys
 import asyncio
 from aiohttp import web, WSMsgType
 import json
@@ -14,26 +14,19 @@ import io
 from PIL import Image
 import gradio as gr
 import cv2
-
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
 logger = logging.getLogger(__name__)
-
 def SIGSEGV_signal_arises(signalNum, stack):
     logger.critical(f"{signalNum} : SIGSEGV arises")
     logger.critical(f"Stack trace: {stack}")
-
 signal.signal(signal.SIGSEGV, SIGSEGV_signal_arises)
-
 from loader import initialize_models
 from engine import Engine, base64_data_uri_to_PIL_Image
 from pathlib import Path
-
 import cv2
-
 # Global constants
 DATA_ROOT = os.environ.get('DATA_ROOT', '/tmp/data')
 MODELS_DIR = os.path.join(DATA_ROOT, "models")
-
 async def setup():
     live_portrait = await initialize_models()
     engine = Engine(live_portrait=live_portrait)
@@ -52,7 +45,6 @@ async def setup():
       
       cap.release()
       return frames
-
     async def return_image(image):
       binary_data = Path(image).read_bytes()
       res = await engine.load_image(binary_data)
@@ -64,7 +56,6 @@ async def setup():
       })
       
       return image
-
     async def return_video(video):
       print(video)
       gr.Info("Extracting frames..")
@@ -72,12 +63,10 @@ async def setup():
       gr.Info("Loading frames..")
       res = await engine.load_frames(frames)
       id = res['u']
-
       height, width, _ = frames[0].shape
       output_file = "output_video.mp4"
       fourcc = cv2.VideoWriter_fourcc(*'mp4v')
       video_writer = cv2.VideoWriter(output_file, fourcc, 24.0, (width, height))
-
       gr.Info("Processing..")
       async for image in engine.transform_video(id, {
               "aaa": -10,
@@ -86,10 +75,8 @@ async def setup():
       }):
         bgr_frame = cv2.cvtColor(np.array(image), cv2.COLOR_BGR2RGB)
         video_writer.write(cv2.cvtColor(bgr_frame, cv2.COLOR_BGR2RGB))
-
       video_writer.release()
       return output_file
-
     with gr.Blocks(title="Retorno de Imagem") as interface:
       gr.Markdown("## 📼 Conversor de Vídeo para Imagem")
       
@@ -104,6 +91,67 @@ async def setup():
           inputs=video_input,
           outputs=image_output,
       )
+    interface.launch(share=True)
+if __name__ == "__main__":
+    asyncio.run(setup())'''
+    
+import sys
+import asyncio
+from aiohttp import web, WSMsgType
+import json
+from json import JSONEncoder
+import numpy as np
+import uuid
+import logging
+import os
+import signal
+from typing import Dict, Any, List, Optional
+import base64
+import io
+from PIL import Image
+import gradio as gr
+import cv2
+
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+logger = logging.getLogger(__name__)
+
+def SIGSEGV_signal_arises(signalNum, stack):
+    logger.critical(f"{signalNum} : SIGSEGV arises")
+    logger.critical(f"Stack trace: {stack}")
+
+signal.signal(signal.SIGSEGV, SIGSEGV_signal_arises)
+
+from loader import initialize_models
+from engine import Engine, base64_data_uri_to_PIL_Image
+from pathlib import Path
+
+import cv2
+
+# Global constants
+DATA_ROOT = os.environ.get('DATA_ROOT', '/tmp/data')
+MODELS_DIR = os.path.join(DATA_ROOT, "models")
+
+async def setup():
+    live_portrait = await initialize_models()
+    engine = Engine(live_portrait=live_portrait)
+
+    async def return_video(video):
+      gr.Info("Processing video..")
+      output = engine.process_video(video, {
+              "aaa": -10,
+              "eee": -10,
+              "woo": -12
+      })
+
+      return output_file
+
+    interface = gr.Interface(
+        fn=return_video,  # Your function to process video
+        inputs=gr.Video(label="Carregue seu vídeo"),
+        outputs=gr.Video(label="Imagem Processada"),
+        title="Retorno de Imagem",
+        description="📼 Conversor de Vídeo para Imagem"
+    )
 
     interface.launch(share=True)