import cv2
import numpy as np
import pandas as pd



class Camera():
    def __init__(self) -> None:
        self.colors = [(0, 0, 255), (0, 255, 0), (255, 0, 0)]
        self.color_names = ["Rot", "Gruen", "Blau"]

        self.lower_red = np.array([80, 160, 150])
        self.upper_red = np.array([255, 255, 255])

        self.lower_green = np.array([40, 50, 160])
        self.upper_green = np.array([80, 255, 255])

        self.lower_blue = np.array([95, 180, 90])
        self.upper_blue = np.array([130, 255, 255])

        self.video = cv2.VideoCapture(0)
        self.start_process = False
        self.correct_field_frame = 0
        self.mean_error = []
        self.scores = {'score_red': 0,
                       'score_green': 0,
                       'score_blue': 0
                       }

    def get_frame(self) -> np.ndarray:
        try:
            _, self.image = self.video.read(1)
        except Exception as err:   
            print("Can not capture the video..\n")
            print(err)
        return self.image
    
    def take_picture(self):
        path = 'src_folder/Game_Images/'
        file_name = 'current_score.png'
        image_path = path+file_name
        cv2.imwrite(image_path, self.image)
        
    def detect_color(self, image):
        hsv_img = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
        count_red, count_green, count_blue= 0,0,0

        for i, color in enumerate(self.colors):
            if i == 0:
                lower = self.lower_red
                upper = self.upper_red
            elif i == 1:
                lower = self.lower_green
                upper = self.upper_green
            elif i == 2:
                lower = self.lower_blue
                upper = self.upper_blue

            mask = cv2.inRange(hsv_img, lower, upper)
            contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

            for contour in contours:
                if  100 < cv2.contourArea(contour):
                    x, y, w, h = cv2.boundingRect(contour)
                    cv2.rectangle(image, (x, y), (x + w, y + h), color, 2)
                    cv2.putText(image, self.color_names[i], (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, color, 2)

                    if i == 0:
                        count_red += 1
                    elif i == 1:
                        count_green += 1
                    elif i == 2:
                        count_blue += 1

        self.scores['score_red'] = count_red
        self.scores['score_green'] = count_green
        self.scores['score_blue'] = count_blue

    def current_score(self, scores: dict):
        return scores

    def range_of_interest(self, frame: np.ndarray, correct_field: int):
        num_windows_in_y = 1
        num_windows_in_x = 3 

        height, width, _ = frame.shape
        roi_height = height/num_windows_in_y
        roi_width = width/num_windows_in_x
        images = []
            
        for x in range(0,num_windows_in_y):
                for y in range(0,num_windows_in_x):
                    tmp_image=frame[int(x*roi_height):int((x+1)*roi_height), int(y*roi_width):int((y+1)*roi_width)]
                    images.append(tmp_image)

        correct_field_frame = images[correct_field]
        return correct_field_frame
    
    def reduce_errors(self, mean_error_list: list):
        for team_color in self.current_score.keys():
            df = pd.DataFrame(mean_error_list)
            total = df[team_color].sum()
            number_of_rows = len(df.index)
            error = total/number_of_rows
            self.current_score[team_color] = round(error)

    def process(self):
        my_camera = Camera()
        square_error = []

        while my_camera.start_process:
            frame = my_camera.get_frame()
            interested_area = my_camera.range_of_interest(frame, my_camera.correct_field_frame)
            my_camera.detect_color(interested_area)   
                
            cv2.line(img=frame, pt1=(frame.shape[1]//3, 0), pt2=(frame.shape[1]//3, frame.shape[0]), color=(0, 0, 0), thickness=2)
            cv2.line(img=frame, pt1=(2 * frame.shape[1]//3, 0), pt2=(2 * frame.shape[1]//3, frame.shape[0]), color=(0, 0, 0), thickness=2)
            cv2.imshow("Kamera 1,2 oder 3", frame)

            print(my_camera.scores)
            square_error.append(my_camera.scores)
            
            if not my_camera.start_process:
                pass

            if cv2.waitKey(1) & 0xFF == ord('q'):
                my_camera.take_picture()
                print(my_camera.scores)
                break

        my_camera.video.release()
        cv2.destroyAllWindows()


# nur zum testen: my_camera.start_process auf True setzen und correct_field_frame zwischen 1 und 3 wählen
# if __name__ == "__main__":
#     my_camera = Camera()
#     my_camera.process()