from flask import Flask, render_template, Response, request, jsonify
import cv2
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")

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():
    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'})

@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)