import pickle
import mediapipe as mp
import cv2
import matplotlib.pyplot as plt
import os

mpHands = mp.solutions.hands
mpDrawing = mp.solutions.drawing_utils
mpDrawingStyles = mp.solutions.drawing_styles

# def brighten_image(img, factor=1.5):
#     return cv2.convertScaleAbs(img, alpha=factor, beta=20)

hands = mpHands.Hands(static_image_mode=True, min_detection_confidence=0.3)

DATADIR = '../letters/asl_alphabet_test'

data = []
labels = []
for imgName in os.listdir(DATADIR):
    dataAux = []

    x_ = []
    y_ = []

    imgPath = os.path.join(DATADIR,imgName)
    print("Reading:", imgPath)

    img = cv2.imread(imgPath)
    if img is None:
        print("Failed to load:", imgPath)
        continue  

    img = cv2.imread(imgPath)
    imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

    results = hands.process(imgRGB)
    if results.multi_hand_landmarks:
        for handLandmarks in results.multi_hand_landmarks:
            
            mpDrawing.draw_landmarks(
                img,  
                handLandmarks,
                mpHands.HAND_CONNECTIONS,
                mpDrawingStyles.get_default_hand_landmarks_style(),
                mpDrawingStyles.get_default_hand_connections_style()
            )

            for i in range(len(handLandmarks.landmark)):
                x = handLandmarks.landmark[i].x
                y = handLandmarks.landmark[i].y

                x_.append(x)
                y_.append(y)

            for i in range(len(handLandmarks.landmark)):
                x = handLandmarks.landmark[i].x
                y = handLandmarks.landmark[i].y
                dataAux.append(x - min(x_))
                dataAux.append(y - min(y_))

        ind = imgName.find("test")

        data.append(dataAux)
        labels.append(imgName[0:ind-1].upper())

        # cv2.imshow("Hand Landmarks", img)
        # cv2.waitKey(0)
        # cv2.destroyAllWindows() 
    
print(labels)

file = open('../processed_data/testData.pickle', 'wb')
pickle.dump({'data': data, 'labels': labels}, file)
file.close()