Update app.py

app.py

@@ -2,16 +2,11 @@ import streamlit as st
 import numpy as np  
 import cv2  
 import tempfile  
-from gradio_client import Client  
+from gradio_client import Client, handle_file  
 from PIL import Image  
 
-# Проверка доступности API  
-api_url = "https://pragnakalp-ocr-image-to-text.hf.space/--replicas/lhzf3/"  
-try:  
-    client = Client(api_url)  
-except Exception as e:  
-    st.error(f"Failed to initialize client: {str(e)}")  
-    st.stop()  
+# Проверка доступности нового API  
+client = Client("yeecin/img2text")  
 
 # Заголовок приложения  
 st.title("Video Frame to Image Description")  
@@ -38,13 +33,20 @@ if uploaded_file is not None:
             pil_image = Image.fromarray(frame_rgb)  
             st.image(pil_image, caption=f"Random Frame {random_frame}")  
 
+            # Сохранение кадра во временный файл для API  
             buf = tempfile.NamedTemporaryFile(suffix='.jpg', delete=False)  
             pil_image.save(buf, format='JPEG')  
             buf.close()  
 
             try:  
-                result = client.predict("PaddleOCR", buf.name, api_name="/predict")  
-                description = result['data']  
+                # Вызов нового API для получения описания  
+                result = client.predict(  
+                    raw_image=handle_file(buf.name),  
+                    model_n="Image Captioning",  
+                    strategy="Nucleus sampling",  
+                    api_name="/predict"  
+                )  
+                description = result  
                 st.success(f"Generated Description: {description}")  
             except Exception as e:  
                 st.error(f"Error: Could not get a response from the model. {str(e)}")