Update app.py

app.py

@@ -1,84 +1,88 @@
 from flask import Flask, render_template, Response, request, jsonify
+import os
 import cv2
-from camera import VideoCamera
-from transformers import CLIPProcessor, CLIPModel
-from PIL import Image
 import numpy as np
+from PIL import Image
+from transformers import CLIPProcessor, CLIPModel
 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")
+# Ensure the uploads folder exists
+os.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True)
+
+# Lazy loading the model
+model = None
+processor = None
+captured_image_path = os.path.join(app.config['UPLOAD_FOLDER'], 'captured.jpg')
+
+
+def load_clip_model():
+    global model, processor
+    if model is None or processor is None:
+        model = CLIPModel.from_pretrained("openai/clip-vit-base-patch16")
+        processor = CLIPProcessor.from_pretrained("openai/clip-vit-base-patch16")
 
-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')
+    return "<h2>Flask App for Image Upload to Instagram is Running!</h2>"
+
+
+@app.route('/health')
+def health():
+    return jsonify({'status': 'healthy'}), 200
 
-@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():
-    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'})
-
-@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'})
+    """
+    This route expects an image to be sent from the frontend (as file)
+    """
+    if 'image' not in request.files:
+        return jsonify({'status': 'error', 'message': 'No image uploaded'}), 400
+
+    file = request.files['image']
+    if file.filename == '':
+        return jsonify({'status': 'error', 'message': 'No file selected'}), 400
+
+    file.save(captured_image_path)
+    return jsonify({'status': 'captured', 'path': captured_image_path})
+
 
 @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)
+    """
+    Processes the image using Hugging Face CLIP and uploads it to Instagram.
+    """
+    if not os.path.exists(captured_image_path):
+        return jsonify({'status': 'error', 'message': 'No captured image'}), 400
+
+    try:
+        load_clip_model()
+
+        image = Image.open(captured_image_path)
         inputs = processor(images=image, return_tensors="pt")
-        outputs = model.get_image_features(**inputs)
-        # Generate a caption (simplified example)
+        _ = model.get_image_features(**inputs)
+
         caption = "Captured image from Flask app! #AI #HuggingFace"
 
-        # Upload to Instagram
-        try:
-            cl = Client()
-            cl.login('SitaraJewellery@sathkrutha.com', 'Sitara@1946')
-            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'})
+        # Instagram upload
+        cl = Client()
+        cl.login('SitaraJewellery@sathkrutha.com', 'Sitara@1946')
+        cl.photo_upload(captured_image_path, caption)
+
+        return jsonify({'status': 'uploaded'})
+
+    except Exception as e:
+        return jsonify({'status': 'error', 'message': str(e)})
+
 
 if __name__ == '__main__':
-    os.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True)
-    app.run(debug=True, host='0.0.0.0', port=5000)
+    import argparse
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--port', type=int, default=7860)
+    args = parser.parse_args()
+
+    app.run(host='0.0.0.0', port=args.port)