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import numpy as np
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import cv2
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from sklearn.externals import joblib
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from face_detector import get_face_detector, find_faces
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def calc_hist(img):
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    """
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    To calculate histogram of an RGB image
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    Parameters
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    ----------
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    img : Array of uint8
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        Image whose histogram is to be calculated
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    Returns
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    -------
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    histogram : np.array
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        The required histogram
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    """
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    histogram = [0] * 3
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    for j in range(3):
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        histr = cv2.calcHist([img], [j], None, [256], [0, 256])
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        histr *= 255.0 / histr.max()
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        histogram[j] = histr
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    return np.array(histogram)
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face_model = get_face_detector()
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clf = joblib.load('models/face_spoofing.pkl')
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cap = cv2.VideoCapture(0)
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sample_number = 1
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count = 0
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measures = np.zeros(sample_number, dtype=np.float)
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while True:
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    ret, img = cap.read()
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    faces = find_faces(img, face_model)
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    measures[count%sample_number]=0
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    height, width = img.shape[:2]
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    for x, y, x1, y1 in faces:
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        roi = img[y:y1, x:x1]
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        point = (0,0)
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        img_ycrcb = cv2.cvtColor(roi, cv2.COLOR_BGR2YCR_CB)
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        img_luv = cv2.cvtColor(roi, cv2.COLOR_BGR2LUV)
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        ycrcb_hist = calc_hist(img_ycrcb)
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        luv_hist = calc_hist(img_luv)
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        feature_vector = np.append(ycrcb_hist.ravel(), luv_hist.ravel())
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        feature_vector = feature_vector.reshape(1, len(feature_vector))
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        prediction = clf.predict_proba(feature_vector)
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        prob = prediction[0][1]
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        measures[count % sample_number] = prob
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        cv2.rectangle(img, (x, y), (x1, y1), (255, 0, 0), 2)
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        point = (x, y-5)
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        # print (measures, np.mean(measures))
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        if 0 not in measures:
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            text = "True"
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            if np.mean(measures) >= 0.7:
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                text = "False"
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                font = cv2.FONT_HERSHEY_SIMPLEX
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                cv2.putText(img=img, text=text, org=point, fontFace=font, fontScale=0.9, color=(0, 0, 255),
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                            thickness=2, lineType=cv2.LINE_AA)
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            else:
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                font = cv2.FONT_HERSHEY_SIMPLEX
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                cv2.putText(img=img, text=text, org=point, fontFace=font, fontScale=0.9,
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                            color=(0, 255, 0), thickness=2, lineType=cv2.LINE_AA)
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    count+=1
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    cv2.imshow('img_rgb', img)
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    if cv2.waitKey(1) & 0xFF == ord('q'):
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            break
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cap.release()
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cv2.destroyAllWindows()
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