Update app.py

app.py

@@ -1,79 +1,83 @@
-import os
 import cv2
 import numpy as np
-from PIL import Image, ImageDraw
-import telebot
+import os
+from telegram import Update
+from telegram.ext import Updater, CommandHandler, MessageHandler, Filters, CallbackContext
 import gradio as gr
 
-# Телеграм-токен
-API_TOKEN = '7458760921:AAFEMNVBuRcM_txnumnwl48u6MlKUS0J4YM'
-bot = telebot.TeleBot(API_TOKEN)
+# Load pre-trained Haar Cascade classifier for face detection
+face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
+
+# List to keep track of processed files
+processed_files = []
 
-# Создание папок для хранения файлов
-os.makedirs('uploads', exist_ok=True)
-os.makedirs('processed', exist_ok=True)
+def start(update: Update, context: CallbackContext) -> None:
+    update.message.reply_text('Send me a photo and I will detect faces!')
 
-# Загрузка классификатора для распознавания лиц
-face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
+def detect_faces(update: Update, context: CallbackContext) -> None:
+    file = update.message.photo[-1].get_file()
+    file.download('photo.jpg')
 
-# Функция для обработки изображения
-def process_image(image_path):
-    img = cv2.imread(image_path)
+    # Read the image
+    img = cv2.imread('photo.jpg')
     gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-    faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))
-    
-    pil_img = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
-    draw = ImageDraw.Draw(pil_img)
-    
-    coords = []
+    faces = face_cascade.detectMultiScale(gray, 1.1, 4)
+
+    # Draw rectangles around faces and annotate coordinates
     for (x, y, w, h) in faces:
-        draw.rectangle([x, y, x + w, y + h], outline="green", width=2)
-        coords.append((x, y, w, h))
-        draw.text((x, y - 10), f"({x}, {y})", fill="green")
-    
-    processed_path = image_path.replace('uploads', 'processed')
-    pil_img.save(processed_path)
-    return processed_path, coords
-
-# Обработчик сообщений с изображениями
-@bot.message_handler(content_types=['photo'])
-def handle_photo(message):
-    file_info = bot.get_file(message.photo[-1].file_id)
-    downloaded_file = bot.download_file(file_info.file_path)
-    
-    file_name = f"uploads/{message.photo[-1].file_id}.jpg"
-    with open(file_name, 'wb') as f:
-        f.write(downloaded_file)
-    
-    processed_path, coords = process_image(file_name)
-    
-    # Отправка обработанного изображения с координатами
-    with open(processed_path, 'rb') as f:
-        bot.send_photo(message.chat.id, f, caption=f"Координаты лиц: {coords}")
-
-# Gradio интерфейс
-def view_files():
-    files = os.listdir('processed')
-    return {file: f"processed/{file}" for file in files}
+        cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
+        cv2.putText(img, f'({x},{y})', (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
+
+    # Save the processed image
+    processed_image_path = 'processed_photo.jpg'
+    cv2.imwrite(processed_image_path, img)
+
+    # Add to processed files list
+    processed_files.append(processed_image_path)
 
-def delete_file(file_name):
-    file_path = f"processed/{file_name}"
+    # Send back the processed image
+    with open(processed_image_path, 'rb') as photo:
+        update.message.reply_photo(photo)
+
+def delete_file(file_path):
     if os.path.exists(file_path):
         os.remove(file_path)
-        return f"Файл {file_name} удалён."
-    return f"Файл {file_name} не найден."
-
-with gr.Blocks() as gr_interface:
-    gr.Markdown("## Управление обработанными изображениями")
-    with gr.Row():
-        gallery = gr.Gallery(label="Обработанные файлы").style(grid=3)
-    with gr.Row():
-        delete_button = gr.Button("Удалить выбранный файл")
-        delete_input = gr.Textbox(label="Имя файла для удаления")
-    delete_output = gr.Textbox(label="Результат удаления")
-
-    delete_button.click(delete_file, inputs=delete_input, outputs=delete_output)
-    gr.Interface(view_files, [], gallery).launch()
-
-# Запуск бота
-bot.polling()
+        return f"{file_path} deleted."
+    return "File not found."
+
+def view_files():
+    return processed_files
+
+def launch_gradio():
+    with gr.Blocks() as demo:
+        gr.Markdown("### Processed Images")
+        
+        file_viewer = gr.File(label="View Processed Files", file_count="multiple")
+        
+        with gr.Row():
+            delete_btn = gr.Button("Delete Selected File")
+            delete_output = gr.Textbox(label="Deletion Status")
+
+            delete_btn.click(fn=delete_file, inputs=file_viewer, outputs=delete_output)
+
+            file_viewer.change(fn=view_files, outputs=file_viewer)
+
+    demo.launch()
+
+def main():
+    # Start the Gradio panel in a separate thread
+    import threading
+    threading.Thread(target=launch_gradio).start()
+
+    updater = Updater("7458760921:AAFEMNVBuRcM_txnumnwl48u6MlKUS0J4YM")
+    dispatcher = updater.dispatcher
+
+    dispatcher.add_handler(CommandHandler("start", start))
+    dispatcher.add_handler(MessageHandler(Filters.photo, detect_faces))
+
+    updater.start_polling()
+    updater.idle()
+
+if __name__ == '__main__':
+    main()
+