opencv_functions.py 文件源码

def faceCrop(targetDir, imgList, color, single_face):
    # Load list of Haar cascades for faces
    faceCascades = load_cascades()

    # Iterate through images
    face_list = []
    for img in imgList:
        if os.path.isdir(img):
            continue
        pil_img = Image.open(img)
        if color:
            cv_img  = cv.cvtColor(np.array(pil_img), cv.COLOR_RGB2BGR)
        else:
            cv_img = np.array(pil_img)
            # Convert to grayscale if this image is actually color
            if cv_img.ndim == 3:
                cv_img = cv.cvtColor(np.array(pil_img), cv.COLOR_BGR2GRAY)

        # Detect all faces in this image
        scaled_img, faces = DetectFace(cv_img, color, faceCascades, single_face, second_pass=False, draw_rects=False)

        # Iterate through faces
        n=1
        for face in faces:
            cropped_cv_img = imgCrop(scaled_img, face, scale=1.0)
            if color:
                cropped_cv_img = rgb(cropped_cv_img)
            fname, ext = os.path.splitext(img)
            cropped_pil_img = Image.fromarray(cropped_cv_img)
            #save_name = loc + '/cropped/' + fname.split('/')[-1] + '_crop' + str(n) + ext
            save_name = targetDir + '/' + fname.split('/')[-1] + '_crop' + str(n) + ext
            cropped_pil_img.save(save_name)
            face_list.append(save_name)
            n += 1

    return face_list

# Add an emoji to an image at a specified point and size
# Inputs: img, emoji are ndarrays of WxHx3
#         faces is a list of (x,y,w,h) tuples for each face to be replaced