python类BLUR的实例源码

voronoi.py 文件源码 项目:Maps 作者: DarkPurple141 项目源码 文件源码 阅读 26 收藏 0 点赞 0 评论 0
def v_fx(screen):
    dims = screen.get_size()
    im1 = pygame.image.tostring(screen,'RGB')
    im = Image.frombytes('RGB',(dims),im1)
    im1 = im.filter(ImageFilter.BLUR)
    im1.save('test.png','PNG')
    return pygame.image.load('test.png')
convert_play.py 文件源码 项目:tefla 作者: litan 项目源码 文件源码 阅读 18 收藏 0 点赞 0 评论 0
def convert_new(fname, target_size):
    print('Processing image: %s' % fname)
    img = Image.open(fname)
    blurred = img.filter(ImageFilter.BLUR)
    ba = np.array(blurred)
    ba_gray = rgb2gray(ba)
    val = filters.threshold_otsu(ba_gray)
    # foreground = (ba_gray > val).astype(np.uint8)
    foreground = closing(ba_gray > val, square(3))
    # kernel = morphology.rectangle(5, 5)
    # foreground = morphology.binary_dilation(foreground, kernel)
    labels = measure.label(foreground)
    properties = measure.regionprops(labels)
    properties = sorted(properties, key=lambda p: p.area, reverse=True)
    # draw_top_regions(properties, 3)
    # return ba
    bbox = properties[0].bbox
    bbox = (bbox[1], bbox[0], bbox[3], bbox[2])
    cropped = img.crop(bbox)
    resized = cropped.resize([target_size, target_size])
    return np.array(resized)
convert_play.py 文件源码 项目:tefla 作者: litan 项目源码 文件源码 阅读 21 收藏 0 点赞 0 评论 0
def convert_new_regions(fname, target_size):
    print('Processing image: %s' % fname)
    img = Image.open(fname)
    blurred = img.filter(ImageFilter.BLUR)
    ba = np.array(blurred)
    ba_gray = rgb2gray(ba)
    val = filters.threshold_otsu(ba_gray)
    # foreground = (ba_gray > val).astype(np.uint8)
    foreground = closing(ba_gray > val, square(3))
    # kernel = morphology.rectangle(5, 5)
    # foreground = morphology.binary_dilation(foreground, kernel)
    labels = measure.label(foreground)
    properties = measure.regionprops(labels)
    properties = sorted(properties, key=lambda p: p.area, reverse=True)
    draw_top_regions(properties, 3)
    return ba
convert.py 文件源码 项目:tefla 作者: litan 项目源码 文件源码 阅读 21 收藏 0 点赞 0 评论 0
def convert(fname, target_size):
    # print('Processing image: %s' % fname)
    img = Image.open(fname)
    blurred = img.filter(ImageFilter.BLUR)
    ba = np.array(blurred)
    ba_gray = rgb2gray(ba)
    val = filters.threshold_otsu(ba_gray)
    # foreground = (ba_gray > val).astype(np.uint8)
    foreground = closing(ba_gray > val, square(3))
    # kernel = morphology.rectangle(5, 5)
    # foreground = morphology.binary_dilation(foreground, kernel)
    labels = measure.label(foreground)
    properties = measure.regionprops(labels)
    properties = sorted(properties, key=lambda p: p.area, reverse=True)
    # draw_top_regions(properties, 3)
    # return ba
    bbox = properties[0].bbox
    bbox = (bbox[1], bbox[0], bbox[3], bbox[2])
    cropped = img.crop(bbox)
    resized = cropped.resize([target_size, target_size])
    return resized
0010.py 文件源码 项目:show-you-my-code 作者: ZsnnsZ 项目源码 文件源码 阅读 18 收藏 0 点赞 0 评论 0
def createPic():
    width = 240
    height = 60
    im = Image.new('RGB', (width, height), (255, 255, 255))
    # ??font??:
    font = ImageFont.truetype('arial.ttf', 35)
    # ??draw??:
    draw = ImageDraw.Draw(im)
    # ??????:
    for x in range(width):
        for y in range(height):
            draw.point((x, y), fill=randColor())
    # ????:
    for t in range(4):
        draw.text((60 * t + 10, 10), randWord(), font=font, fill=randColor2())
    # ????
    im = im.filter(ImageFilter.BLUR)
    im.show()
    im.save('code.jpg', 'jpeg')
aHash.py 文件源码 项目:Learn-to-identify-similar-images 作者: MashiMaroLjc 项目源码 文件源码 阅读 16 收藏 0 点赞 0 评论 0
def classfiy_aHash(image1,image2,size=(8,8),exact=25):
    ''' 'image1' and 'image2' is a Image Object.
    You can build it by 'Image.open(path)'.
    'Size' is parameter what the image will resize to it and then image will be compared by the algorithm.
    It's 8 * 8 when it default.  
    'exact' is parameter for limiting the Hamming code between 'image1' and 'image2',it's 25 when it default.
    The result become strict when the exact become less. 
    This function return the true when the 'image1'  and 'image2' are similar. 
    '''
    image1 = image1.resize(size).convert('L').filter(ImageFilter.BLUR)
    image1 = ImageOps.equalize(image1)
    code1 = getCode(image1, size)
    image2 = image2.resize(size).convert('L').filter(ImageFilter.BLUR)
    image2 = ImageOps.equalize(image2)
    code2 = getCode(image2, size)

    assert len(code1) == len(code2),"error"

    return compCode(code1, code2)<=exact
similar_image.py 文件源码 项目:hacker-scripts 作者: restran 项目源码 文件源码 阅读 19 收藏 0 点赞 0 评论 0
def classify_ahash(cls, image1, image2, size=(8, 8), exact=25):
        """ 'image1' and 'image2' is a Image Object.
        You can build it by 'Image.open(path)'.
        'Size' is parameter what the image will resize to it and then image will be compared by the algorithm.
        It's 8 * 8 when it default.
        'exact' is parameter for limiting the Hamming code between 'image1' and 'image2',it's 25 when it default.
        The result become strict when the exact become less.
        This function return the true when the 'image1'  and 'image2' are similar.
        """
        image1 = image1.resize(size).convert('L').filter(ImageFilter.BLUR)
        image1 = ImageOps.equalize(image1)
        code1 = cls.get_code(image1, size)
        image2 = image2.resize(size).convert('L').filter(ImageFilter.BLUR)
        image2 = ImageOps.equalize(image2)
        code2 = cls.get_code(image2, size)

        assert len(code1) == len(code2), "error"

        return cls.compare_code(code1, code2)
phedited.py 文件源码 项目:IV 作者: collinmutembei 项目源码 文件源码 阅读 18 收藏 0 点赞 0 评论 0
def apply_effects(image, effects):
    """method to apply effects to original image from list of effects
    """
    for effect in effects:
        gray = ImageOps.grayscale(image)
        # dictionary with all the availble effects
        all_effects = {
            'BLUR': image.filter(ImageFilter.BLUR),
            'CONTOUR': image.filter(ImageFilter.CONTOUR),
            'EMBOSS': image.filter(ImageFilter.EMBOSS),
            'SMOOTH': image.filter(ImageFilter.SMOOTH),
            'HULK': ImageOps.colorize(gray, (0, 0, 0, 0), '#00ff00'),
            'FLIP': ImageOps.flip(image),
            'MIRROR': ImageOps.mirror(image),
            'INVERT': ImageOps.invert(image),
            'SOLARIZE': ImageOps.solarize(image),
            'GREYSCALE': ImageOps.grayscale(image),

        }
        phedited = all_effects[effect]
        image = phedited
    return phedited
convert.py 文件源码 项目:melanoma-transfer 作者: learningtitans 项目源码 文件源码 阅读 21 收藏 0 点赞 0 评论 0
def convert(fname, crop_size):
    img = Image.open(fname)

    blurred = img.filter(ImageFilter.BLUR)
    ba = np.array(blurred)
    h, w, _ = ba.shape

    if w > 1.2 * h:
        left_max = ba[:, : w // 32, :].max(axis=(0, 1)).astype(int)
        right_max = ba[:, - w // 32:, :].max(axis=(0, 1)).astype(int)
        max_bg = np.maximum(left_max, right_max)

        foreground = (ba > max_bg + 10).astype(np.uint8)
        bbox = Image.fromarray(foreground).getbbox()

        if bbox is None:
            print('bbox none for {} (???)'.format(fname))
        else:
            left, upper, right, lower = bbox
            # if we selected less than 80% of the original
            # height, just crop the square
            if right - left < 0.8 * h or lower - upper < 0.8 * h:
                print('bbox too small for {}'.format(fname))
                bbox = None
    else:
        bbox = None

    if bbox is None:
        bbox = square_bbox(img)

    cropped = img.crop(bbox)
    resized = cropped.resize([crop_size, crop_size])
    return resized
image_test.py 文件源码 项目:base_function 作者: Rockyzsu 项目源码 文件源码 阅读 21 收藏 0 点赞 0 评论 0
def base_usage():
    im=Image.open("data/original.jpg")
    im2=Image.open("data/original.jpg")
    print im
    im=im.convert('L')
    print im
    image_data = im.getdata()
    print image_data
    #im.show()
    (w,h)=im.size
    print w,h
    im.thumbnail((w/2,h/2))
    im.save("data/small.jpg",'jpeg')
    im2.filter(ImageFilter.BLUR)
    im2.save("data/blur3.jpg",'jpeg')
utils.py 文件源码 项目:dogsVScats 作者: prajwalkr 项目源码 文件源码 阅读 19 收藏 0 点赞 0 评论 0
def blur(arr, tf):
    img = to_PIL(arr, tf)
    if tf: return img.filter(ImageFilter.BLUR)
    return to_theano(img.filter(ImageFilter.BLUR))
convert_play.py 文件源码 项目:tefla 作者: litan 项目源码 文件源码 阅读 21 收藏 0 点赞 0 评论 0
def convert(fname, target_size):
    img = Image.open(fname)

    blurred = img.filter(ImageFilter.BLUR)
    ba = np.array(blurred)
    h, w, _ = ba.shape

    if w > 1.2 * h:
        left_max = ba[:, : w // 32, :].max(axis=(0, 1)).astype(int)
        right_max = ba[:, - w // 32:, :].max(axis=(0, 1)).astype(int)
        max_bg = np.maximum(left_max, right_max)

        foreground = (ba > max_bg + 10).astype(np.uint8)
        bbox = Image.fromarray(foreground).getbbox()

        if bbox is None:
            print('bbox none for {} (???)'.format(fname))
        else:
            left, upper, right, lower = bbox
            # if we selected less than 80% of the original
            # height, just crop the square
            if right - left < 0.8 * h or lower - upper < 0.8 * h:
                print('bbox too small for {}'.format(fname))
                bbox = None
    else:
        bbox = None

    if bbox is None:
        bbox = square_bbox(img, fname)

    cropped = img.crop(bbox)
    resized = cropped.resize([target_size, target_size])
    return np.array(resized)
convert_play.py 文件源码 项目:tefla 作者: litan 项目源码 文件源码 阅读 18 收藏 0 点赞 0 评论 0
def crop_image(fname,target_size):
    print('Processing image: %s' % fname)

    #otsu thresholding
    img = Image.open(fname)
    blurred = img.filter(ImageFilter.BLUR)
    ba = np.array(blurred)
    gray_image = cv2.cvtColor(ba, cv2.COLOR_BGR2GRAY)
    retval2, threshold2 = cv2.threshold(gray_image, 125, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)

    #storing white pixel in  each row and column in two arrays
    #these arrays are later used to find boundaries for cropping image
    row_white_pixel_count=np.count_nonzero(threshold2,axis=1)
    col_white_pixel_count=np.count_nonzero(threshold2,axis=0)

    #find x,y,w,h for cropping image
    y=find_boundary(row_white_pixel_count,col_white_pixel_count.size)
    h=find_boundary_reverse(row_white_pixel_count,col_white_pixel_count.size)
    x=find_boundary(col_white_pixel_count,row_white_pixel_count.size)
    w=find_boundary_reverse(col_white_pixel_count,row_white_pixel_count.size)
    crop_array = ba[y:h, x:w]

    #resize the image
    crop_img=Image.fromarray(crop_array)
    resized = crop_img.resize([target_size, target_size])


    #uncomment below line to see histogram of both white pixel vs rows and white pixel vs columns
    subplots(threshold2, row_white_pixel_count, col_white_pixel_count, crop_img)
    return resized
pyqt.py 文件源码 项目:livre-python 作者: HE-Arc 项目源码 文件源码 阅读 19 收藏 0 点赞 0 评论 0
def blurImage(self):
        """Floute l'image à l'aide de PIL puis affiche le résultat."""
        self.image = self.image.filter(ImageFilter.BLUR)
        self.displayImage()
process_image.py 文件源码 项目:inception-face-shape-classifier 作者: adonistio 项目源码 文件源码 阅读 27 收藏 0 点赞 0 评论 0
def blur_img(imdir,outdir):
    im = Image.open(imdir)
    out_filename = outdir
    out_img = im.filter(ImageFilter.BLUR).save(out_filename, 'JPEG', quality=100)
eugreatsingers.py 文件源码 项目:pudzu 作者: Udzu 项目源码 文件源码 阅读 16 收藏 0 点赞 0 评论 0
def labelfn(c, w, h):
    if c not in df.index:
        return None
    x = Image.from_text_bounded(df.name[c], (w, h), 18, papply(arial, bold=True), padding=4, max_width=w, align="center", fg="black")
    y = x.replace_color("black", "white", ignore_alpha=True).filter(ImageFilter.BLUR)
    return y.place(x)
test_models.py 文件源码 项目:nider 作者: pythad 项目源码 文件源码 阅读 23 收藏 0 点赞 0 评论 0
def test_draw_on_image_with_filters(self,
                                        _draw_content_mock,
                                        _save,
                                        filter_mock):
        filters = (ImageFilter.BLUR, ImageFilter.GaussianBlur(2))
        with create_test_image():
            filter_mock.return_value = PIL_Image.open('test.png')
            self.img.draw_on_image(
                image_path=os.path.abspath('test.png'),
                image_filters=filters)
        self.assertTrue(filter_mock.called)
        self.assertTrue(_draw_content_mock.called)
convert.py 文件源码 项目:tefla 作者: openAGI 项目源码 文件源码 阅读 20 收藏 0 点赞 0 评论 0
def convert(fname, target_size=512):
    img = Image.open(fname).convert('RGB')

    blurred = img.filter(ImageFilter.BLUR)
    ba = np.array(blurred)
    h, w, _ = ba.shape

    if w > 1.2 * h:
        left_max = ba[:, : w // 32, :].max(axis=(0, 1)).astype(int)
        right_max = ba[:, - w // 32:, :].max(axis=(0, 1)).astype(int)
        max_bg = np.maximum(left_max, right_max)

        foreground = (ba > max_bg + 10).astype(np.uint8)
        bbox = Image.fromarray(foreground).getbbox()

        if bbox is None:
            print('bbox none for {} (???)'.format(fname))
        else:
            left, upper, right, lower = bbox
            # if we selected less than 80% of the original
            # height, just crop the square
            if right - left < 0.8 * h or lower - upper < 0.8 * h:
                print('bbox too small for {}'.format(fname))
                bbox = None
    else:
        bbox = None

    if bbox is None:
        bbox = square_bbox(img, fname)

    cropped = img.crop(bbox)
    resized = cropped.resize([target_size, target_size])
    return resized
convert_seg.py 文件源码 项目:tefla 作者: openAGI 项目源码 文件源码 阅读 16 收藏 0 点赞 0 评论 0
def convert(image_fname, label_fname, target_size):
    img = Image.open(image_fname)
    label = Image.open(label_fname)

    blurred = img.filter(ImageFilter.BLUR)
    ba = np.array(blurred)
    h, w, _ = ba.shape

    if w > 1.2 * h:
        left_max = ba[:, : w // 32, :].max(axis=(0, 1)).astype(int)
        right_max = ba[:, - w // 32:, :].max(axis=(0, 1)).astype(int)
        max_bg = np.maximum(left_max, right_max)

        foreground = (ba > max_bg + 10).astype(np.uint8)
        bbox = Image.fromarray(foreground).getbbox()

        if bbox is None:
            print('bbox none for {} (???)'.format(image_fname))
        else:
            left, upper, right, lower = bbox
            # if we selected less than 80% of the original
            # height, just crop the square
            if right - left < 0.8 * h or lower - upper < 0.8 * h:
                print('bbox too small for {}'.format(image_fname))
                bbox = None
    else:
        bbox = None

    if bbox is None:
        bbox = square_bbox(img, image_fname)

    cropped_img = img.crop(bbox)
    cropped_label = label.crop(bbox)
    resized_img = cropped_img.resize([target_size, target_size])
    resized_label = cropped_label.resize([target_size, target_size])
    return resized_img, resized_label
create_synthetic_imgs.py 文件源码 项目:img_augmentation 作者: huvers 项目源码 文件源码 阅读 25 收藏 0 点赞 0 评论 0
def make_blur_img(file_name, path_dir):
    file_path = path_dir + '/' + file_name
    img = Image.open('%s' % file_path)
    img.filter(ImageFilter.BLUR).save(path_dir + '/' + '%02s_blur'
                                      % file_name.translate(None, '.png') + '.png', "PNG")
    return
noise.py 文件源码 项目:road_simulator 作者: vinzeebreak 项目源码 文件源码 阅读 22 收藏 0 点赞 0 评论 0
def call(self, img):

        if img is None: raise ValueError('img is None')

        im_n = img.copy()

        gauss_blur_low, gauss_blur_high = 0, self.gauss_blur
        blur_low, blur_high = gauss_blur_high, gauss_blur_high + self.blur
        smooth_low, smooth_high = blur_high, blur_high + self.smooth
        smooth_more_low, smooth_more_high = smooth_high, smooth_high + self.smooth_more
        rank_low, rank_high = smooth_more_high, smooth_more_high + self.rank_filter

        r = random()
        if gauss_blur_low <= r <= gauss_blur_high:
            im_n = im_n.filter(ImageFilter.GaussianBlur(1))
        elif blur_low < r <= blur_high:
            im_n = im_n.filter(ImageFilter.BLUR)
        elif smooth_low < r <= smooth_high:
            im_n = im_n.filter(ImageFilter.SMOOTH)
        elif smooth_more_low < r <= smooth_more_high:
            im_n = im_n.filter(ImageFilter.SMOOTH_MORE)
        elif rank_low < r <= rank_high:
            im_n = im_n.filter(ImageFilter.RankFilter(size=3, rank=7))
        else:
            pass
        return im_n
test_filter.py 文件源码 项目:imgpy 作者: embali 项目源码 文件源码 阅读 25 收藏 0 点赞 0 评论 0
def test_filter(path, image):
    with Img(fp=path(image['sub'])) as src, TemporaryFile() as tf:
        if 'mode' in image:
            src.convert(image['mode'])

        src.filter(ImageFilter.BLUR)
        src.save(fp=tf)
        with Img(fp=tf) as dest:
            assert (dest.width, dest.height, dest.frame_count) == (
                src.width, src.height, src.frame_count)
verify_image.py 文件源码 项目:burnell-web 作者: BurnellLiu 项目源码 文件源码 阅读 19 收藏 0 点赞 0 评论 0
def generate_verify_image(font_path):
    """
    ???????
    :param font_path: ???????????
    :return: ????????base64?????
    """
    width = 60 * 4
    height = 60
    image = Image.new('RGB', (width, height), (255, 255, 255))
    # ??Font??:
    font = ImageFont.truetype(font_path, 36)
    # ??Draw??:
    draw = ImageDraw.Draw(image)
    # ??????:
    for x in range(width):
        for y in range(height):
            draw.point((x, y), fill=rand_background_color())

    # ????:
    rand_str = rand_char()
    rand_str += rand_char()
    rand_str += rand_char()
    rand_str += rand_char()
    for t in range(4):
        draw.text((60 * t + 10, 10), rand_str[t], font=font, fill=rand_text_color())

    # ??:
    image = image.filter(ImageFilter.BLUR)

    file_name = './static/img/' + str(time.time())
    file_name += '.jpg'
    image.save(file_name, 'jpeg')

    f = open(file_name, 'rb')
    str_image = b'data:image/jpeg;base64,'
    str_image += base64.b64encode(f.read())
    f.close()
    os.remove(file_name)

    return rand_str, bytes.decode(str_image)
pHash.py 文件源码 项目:Learn-to-identify-similar-images 作者: MashiMaroLjc 项目源码 文件源码 阅读 23 收藏 0 点赞 0 评论 0
def classify_DCT(image1,image2,size=(32,32),part_size=(8,8)):
    """ 'image1' and 'image2' is a Image Object.
    You can build it by 'Image.open(path)'.
    'Size' is parameter what the image will resize to it and then image will be compared by the pHash.
    It's 32 * 32 when it default. 
    'part_size' is a size of a part of the matrix after Discrete Cosine Transform,which need to next steps.
    It's 8 * 8 when it default. 

    The function will return the hamming code,less is correct. 
    """
    assert size[0]==size[1],"size error"
    assert part_size[0]==part_size[1],"part_size error"

    image1 = image1.resize(size).convert('L').filter(ImageFilter.BLUR)
    image1 = ImageOps.equalize(image1)
    matrix = get_matrix(image1)
    DCT_matrix = DCT(matrix)
    List = sub_matrix_to_list(DCT_matrix, part_size)
    middle = get_middle(List)
    code1 = get_code(List, middle)


    image2 = image2.resize(size).convert('L').filter(ImageFilter.BLUR)
    image2 = ImageOps.equalize(image2)
    matrix = get_matrix(image2)
    DCT_matrix = DCT(matrix)
    List = sub_matrix_to_list(DCT_matrix, part_size)
    middle = get_middle(List)
    code2 = get_code(List, middle)



    return comp_code(code1, code2)
DigitClassifier.py 文件源码 项目:DigitClassifier 作者: ommadawn46 项目源码 文件源码 阅读 17 收藏 0 点赞 0 评论 0
def recognize(self):
        # ???????????????????
        img = self.input_canvas.getImage().filter(ImageFilter.BLUR).convert('L')
        img.thumbnail((28, 28), getattr(Image, 'ANTIALIAS'))
        img = img.point(lambda x: 255 - x)
        input = np.asarray(img).ravel()
        result = self.nn.test([input / 255.0], np.zeros(10))[0]
        num = max(enumerate(result), key=lambda x: x[1])[0]
        self.result_label.configure(text = str(num))
        print(num, result)
CAPTCHA.py 文件源码 项目:scripts-for-bupt 作者: Forec 项目源码 文件源码 阅读 26 收藏 0 点赞 0 评论 0
def make( numbers, width = 400, height = 200):
    strs = ''.join(random.sample('abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789', numbers))
    im = Image.new( 'RGB', (width, height ), (255,255,255))
    draw = ImageDraw.Draw(im)
    font = ImageFont.truetype('verdana.ttf',width//numbers)
    font_width , font_height = font.getsize(strs)
    strs_len = len(strs)
    x = (width - font_width) // 2
    y = (height - font_height ) //2
    total_dex = 0
    for i in strs:
        draw.text((x,y), i, random_col(), font)
        temp = random.randint(-23,23)
        total_dex += temp
        im = im.rotate(temp)
        draw = ImageDraw.Draw(im)
        x += font_width/strs_len
    im = im.rotate(-total_dex)
    draw = ImageDraw.Draw(im)
    draw.line(
        [(random.randint(0,width//numbers),
        random.randint(0,height//numbers)
        ),
        (random.randint(width//numbers*(numbers-1),width),
        random.randint(height//numbers*(numbers-1),height)
        )],
        fill = random_col(),
        width = numbers+1)
    draw.line(
        [(random.randint(0,width//numbers),
            random.randint(height//numbers*(numbers-1),height)
        ),
        (random.randint(width//(numbers-1)*(numbers-2),width),
        random.randint(0,height//(numbers-1))
        )],
        fill = random_col(),
        width = numbers+1)
    draw.line(
        [(random.randint(width//4*3,width),
            random.randint(height//4*3,height)
        ),
        (random.randint(width//3*2,width),
        random.randint(0,height//3)
        )],
        fill = random_col(),
        width = numbers + 1)
    for x in range(width):
        for y in range(height):
            col = im.getpixel((x,y))
            if col == (255,255,255) or col == (0,0,0):
                draw.point((x,y), fill = random_col())
    im = im.filter(ImageFilter.BLUR)
    im.save('out.jpg')


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