Update app.py

app.py

@@ -1,40 +1,84 @@
-from flask import Flask, render_template, request, jsonify
-import os
+from flask import Flask, render_template, Response, request, jsonify
 import cv2
-import base64
-import requests
+from camera import VideoCamera
+from transformers import CLIPProcessor, CLIPModel
+from PIL import Image
+import numpy as np
+from instagrapi import Client
+import os
 
 app = Flask(__name__)
+app.config['UPLOAD_FOLDER'] = 'uploads'
+camera = None
+captured_image = None
+
+# Initialize Hugging Face CLIP model
+model = CLIPModel.from_pretrained("openai/clip-vit-base-patch16")
+processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch16")
 
-# Instagram credentials (use your Instagram bot or automation method here)
-INSTAGRAM_USERNAME = 'your_username'
-INSTAGRAM_PASSWORD = 'your_password'
+def gen(camera):
+    while True:
+        frame = camera.get_frame()
+        yield (b'--frame\r\n'
+               b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n\r\n')
 
 @app.route('/')
 def index():
     return render_template('index.html')
 
+@app.route('/video_feed')
+def video_feed():
+    global camera
+    if camera is None:
+        camera = VideoCamera()
+    return Response(gen(camera), mimetype='multipart/x-mixed-replace; boundary=frame')
+
 @app.route('/capture', methods=['POST'])
 def capture():
-    image_data = request.form['image']
-    # Decode the image from base64 to save it
-    img_data = base64.b64decode(image_data.split(',')[1])
-    with open("static/images/captured_image.jpg", "wb") as f:
-        f.write(img_data)
-    
-    return jsonify({"message": "Image captured!"})
-
-@app.route('/post_to_instagram', methods=['POST'])
-def post_to_instagram():
-    # Assuming you're using instabot for posting to Instagram
-    from instabot import Bot
-    bot = Bot()
-    bot.login(username=INSTAGRAM_USERNAME, password=INSTAGRAM_PASSWORD)
-    image_path = "static/images/captured_image.jpg"
-    bot.upload_photo(image_path, caption="Your Image Caption Here")
-    
-    return jsonify({"message": "Image posted to Instagram!"})
+    global captured_image, camera
+    if camera:
+        captured_image = camera.get_frame()
+        img_array = np.frombuffer(captured_image, np.uint8)
+        img = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
+        cv2.imwrite(os.path.join(app.config['UPLOAD_FOLDER'], 'captured.jpg'), img)
+    return jsonify({'status': 'captured'})
 
-if __name__ == '__main__':
-    app.run(debug=False)  # Turn off debug mode for production
+@app.route('/switch_camera', methods=['POST'])
+def switch_camera():
+    global camera
+    camera_type = request.json.get('camera_type', 'user')  # 'user' for front, 'environment' for back
+    if camera:
+        camera.switch_camera(camera_type)
+    return jsonify({'status': 'switched'})
 
+@app.route('/retake', methods=['POST'])
+def retake():
+    global captured_image
+    captured_image = None
+    return jsonify({'status': 'retake'})
+
+@app.route('/upload', methods=['POST'])
+def upload():
+    global captured_image
+    if captured_image:
+        # Process image with Hugging Face CLIP
+        img_path = os.path.join(app.config['UPLOAD_FOLDER'], 'captured.jpg')
+        image = Image.open(img_path)
+        inputs = processor(images=image, return_tensors="pt")
+        outputs = model.get_image_features(**inputs)
+        # Generate a caption (simplified example)
+        caption = "Captured image from Flask app! #AI #HuggingFace"
+
+        # Upload to Instagram
+        try:
+            cl = Client()
+            cl.login('YOUR_INSTAGRAM_USERNAME', 'YOUR_INSTAGRAM_PASSWORD')
+            cl.photo_upload(img_path, caption=caption)
+            return jsonify({'status': 'uploaded'})
+        except Exception as e:
+            return jsonify({'status': 'error', 'message': str(e)})
+    return jsonify({'status': 'error', 'message': 'No image captured'})
+
+if __name__ == '__main__':
+    os.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True)
+    app.run(debug=True, host='0.0.0.0', port=5000)