import cv2
import streamlit as st
from streamlit_webrtc import webrtc_streamer
import numpy as np
from PIL import Image
from Moildev import Moildev
import threading


class demo_app:
    def __init__(self):
        # self.dev = 'Raspi_Cam.json'
        self.moildev = Moildev()

    def brighten_image(self, image, amount):
        img_bright = cv2.convertScaleAbs(image, beta=amount)
        return img_bright

    def anypoint_image(self, image, alpha, beta, zoom, mode):
        any_image = self.moildev.anypoint(image, alpha, beta, zoom, mode)
        return any_image

    def main_loop(self):
        st.title("MoilDev Demo App")
        st.subheader("This app allows you to play with Image filters!")
        st.text("We use OpenCV and Streamlit for this demo")

        # radio
        source = st.sidebar.radio('Sources:', ('image', 'video', 'stream'))

        if source == 'image':
            # slider
            zoom = st.sidebar.slider("Zoom", min_value=1.0, max_value=3.5, value=1.2)
            alpha = st.sidebar.slider("Alpha", min_value=0.0, max_value=180.0, value=60.0)
            beta = st.sidebar.slider("Beta", min_value=0.0, max_value=180.0, value=60.0)
            brightness_amount = st.sidebar.slider("Brightness", min_value=-50, max_value=50, value=0)

            # checkbox
            mode_filter = st.sidebar.checkbox('Car Mode')

            # upload json
            json_file = st.file_uploader("Upload Your Parameter", type=['json'])
            if not json_file:
                return None

            if json_file:
                dev = json_file.name

            self.moildev = Moildev(dev)

            image_file = st.file_uploader("Upload Your Image", type=['jpg', 'png', 'jpeg'])
            if not image_file:
                return None

            original_image = Image.open(image_file)
            original_image = np.array(original_image)

            if mode_filter == 1:
                processed_image = self.anypoint_image(original_image, alpha=alpha, beta=beta, zoom=zoom, mode=1)

            else:
                processed_image = self.anypoint_image(original_image, alpha=alpha, beta=beta, zoom=zoom, mode=2)

            processed_image = self.brighten_image(processed_image, brightness_amount)
            st.text("Original Image vs Processed Image")
            st.image([original_image, processed_image])

        if source == 'video':
            # slider
            zoom = st.sidebar.slider("Zoom", min_value=1.0, max_value=3.5, value=1.2)
            alpha = st.sidebar.slider("Alpha", min_value=0.0, max_value=180.0, value=60.0)
            beta = st.sidebar.slider("Beta", min_value=0.0, max_value=180.0, value=60.0)
            brightness_amount = st.sidebar.slider("Brightness", min_value=-50, max_value=50, value=0)

            # checkbox
            mode_filter = st.sidebar.checkbox('Car Mode')




        if source == 'stream':

            # slider
            zoom = st.sidebar.slider("Zoom", min_value=1.0, max_value=3.5, value=1.2)
            alpha = st.sidebar.slider("Alpha", min_value=0.0, max_value=360.0, value=60.0)
            beta = st.sidebar.slider("Beta", min_value=0.0, max_value=360.0, value=60.0)

            # checkbox
            mode_filter = st.sidebar.checkbox('Car Mode')

            lock = threading.Lock()
            img_container = {"img": None}

            def video_frame_callback(frame):
                img = frame.to_ndarray(format="bgr24")
                with lock:
                    img_container["img"] = img
                return frame

            ctx = webrtc_streamer(key="example", video_frame_callback=video_frame_callback)
            vsn_place = st.empty()

            while ctx.state.playing:
                cv2.waitKey(10)
                with lock:
                    img = img_container["img"]
                if img is None:
                    continue

                if mode_filter == 1:
                    processed_image = self.anypoint_image(img, alpha=alpha, beta=beta, zoom=zoom, mode=1)
                    vsn_place.image(processed_image)

                else:
                    processed_image = self.anypoint_image(img, alpha=alpha, beta=beta, zoom=zoom, mode=2)
                    vsn_place.image(processed_image)


if __name__ == '__main__':
    da = demo_app()
    da.main_loop()