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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()
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