我们从Python开源项目中，提取了以下32个代码示例，用于说明如何使用PIL.ImageEnhance.Contrast()。
def velocity_ocr(image,coords,f1app): # crop and convert image to greyscale img = Image.fromarray(image).crop(coords).convert('L') img = img.resize([img.width*2,img.height*2]) if f1app: # filters for video from the f1 app img = ImageEnhance.Brightness(img).enhance(3.0) img = ImageEnhance.Contrast(img).enhance(2.0) else: # filters for onboard video graphic img = ImageEnhance.Brightness(img).enhance(0.1) img = ImageEnhance.Contrast(img).enhance(2.0) img = ImageEnhance.Contrast(img).enhance(4.0) img = ImageEnhance.Brightness(img).enhance(0.2) img = ImageEnhance.Contrast(img).enhance(16.0) try: # vel = pytesseract.image_to_string(img,config='digits') vel = pytesseract.image_to_string(img) except UnicodeDecodeError: vel = -1 return vel
def account_by_qr(qr_file): qr = qrtools.QR() qr.decode(qr_file) # Try to increase contrast if not recognized if ('xrb_' not in qr.data): image = Image.open(qr_file) contrast = ImageEnhance.Contrast(image) image = contrast.enhance(7) image.save('{0}'.format(qr_file.replace('.jpg', '_.jpg')), 'JPEG') qr2 = qrtools.QR() qr2.decode('{0}'.format(qr_file.replace('.jpg', '_.jpg'))) #print(qr2.data) qr = qr2 returning = qr.data.replace('xrb:', '').replace('raiblocks://', '').replace('raiblocks:', '').split('?') # parsing amount if (len(returning) > 1): if ('amount=' in returning[1]): returning[1] = returning[1].replace('amount=', '') # don't use empty if (len(returning[1]) == 0): returning.pop() else: returning.pop() return returning
def maskFace(self, frame_image, face): img1 = cv2.imread(self.__class__.mask_path, cv2.IMREAD_UNCHANGED); elements = cv2.imread(self.__class__.mask_elements_path, cv2.IMREAD_UNCHANGED); h, status = cv2.findHomography(self.average_points, np.array(self.getFacePoints(face))) mask = self.getTransPIL(cv2.warpPerspective(img1, h, (frame_image.width,frame_image.height))) mask_elements = self.getTransPIL(cv2.warpPerspective(elements, h, (frame_image.width,frame_image.height))) enhancer = ImageEnhance.Color(frame_image) enhanced = enhancer.enhance(0.1) enhancer = ImageEnhance.Brightness(enhanced) enhanced = enhancer.enhance(1.2) enhancer = ImageEnhance.Contrast(enhanced) enhanced = enhancer.enhance(1.2) frame_image.paste(enhanced, (0,0), mask) frame_image.paste(mask_elements, (0,0), mask_elements)
def change_contrast(image, contrast=1.0): """ Change contrast of image. >>> image = np.eye(3, dtype='uint8') * 255 >>> change_contrast(image, 0.5) array([[170, 42, 42], [ 42, 170, 42], [ 42, 42, 170]], dtype=uint8) See http://pillow.readthedocs.io/en/3.1.x/reference/ImageEnhance.html#PIL.ImageEnhance.Contrast :param numpy array image: Numpy array with range [0,255] and dtype 'uint8'. :param float contrast: Contrast [0, 1] :return: Image with changed contrast :rtype: numpy array with range [0,255] and dtype 'uint8' """ return enhance(image, ie.Contrast, contrast)
def contrast_transform(img, contrast_min=0.8, contrast_max=1.2): """Transform input image contrast Transform the input image contrast by a factor returned by a unifrom distribution with `contarst_min` and `contarst_max` as params Args: img: `ndarray`, input image contrast_min: float, minimum contrast for transformation contrast_max: float, maximum contrast for transformation Returns: `ndarray`, contrast enhanced image """ if isinstance(img, (np.ndarray)): img = Image.fromarray(img) contrast_param = np.random.uniform(contrast_min, contrast_max) t_img = ImageEnhance.Contrast(img).enhance(contrast_param) return np.array(t_img)
def produce(txt,img,ver=5,err_crt = qrcode.constants.ERROR_CORRECT_H,bri = 1.0, cont = 1.0,\ colourful = False, rgba = (0,0,0,255),pixelate = False): """Produce QR code :txt: QR text :img: Image path / Image object :ver: QR version :err_crt: QR error correct :bri: Brightness enhance :cont: Contrast enhance :colourful: If colourful mode :rgba: color to replace black :pixelate: pixelate :returns: list of produced image """ if type(img) is Image.Image: pass elif type(img) is str: img = Image.open(img) else: return [] frames = [produce_impl(txt,frame.copy(),ver,err_crt,bri,cont,colourful,rgba,pixelate) for frame in ImageSequence.Iterator(img)] return frames
def getJitteredImgs(self, img, num, maxRot=(-5.0, 5.0), maxTranslate=(-2.0, 2.0), maxScale=(-0.1, 0.1), augmentColor=False): """ Take img and jitter it :return: a list of all jittered images """ cx = img.size[0] / 2 cy = img.size[1] / 2 tMats = self.getJitteredParams(center=(cx, cy), num=num, maxRot=maxRot, maxTranslate=maxTranslate, maxScale=maxScale) imgs = [] for i in range(len(tMats)): t = tMats[i] imgT = self.transformImg(img, t) if augmentColor: # jitter colors color = ImageEnhance.Color(imgT) imgT = color.enhance(self.rng.uniform(0.7, 1)) # jitter contrast contr = ImageEnhance.Contrast(imgT) imgT = contr.enhance(self.rng.uniform(0.7, 1)) # jitter brightness bright = ImageEnhance.Brightness(imgT) imgT = bright.enhance(self.rng.uniform(0.7, 1)) # add noise im = numpy.asarray(imgT).astype('int') + numpy.rint(self.rng.normal(0, 4, numpy.asarray(imgT).shape)).astype('int') im = numpy.clip(im, 0, 255).astype('uint8') imgT = Image.fromarray(im) # add image imgs.append(imgT) return imgs, tMats
def do_contrast(self): """usage: contrast <image:pic1> Enhance contrast in the top image. """ from PIL import ImageEnhance factor = float(self.do_pop()) image = self.do_pop() enhancer = ImageEnhance.Contrast(image) self.push(enhancer.enhance(factor))
def random_contrast_shift(arr, tf): img = to_PIL(arr, tf) if tf: return ImageEnhance.Contrast(img).enhance(np.random.uniform(0.8, 1.2)) return to_theano(ImageEnhance.Contrast(img).enhance(np.random.uniform(0.8, 1.2)))
def ocr_appendcode(): #????? image = Image.open("./data/token.jpg") image = image.convert("L") remove_noise.clearNoise(image,127,2,1) #ocr?? enhancer = ImageEnhance.Contrast(image) image_enhancer = enhancer.enhance(4) text = pytesser.image_to_string(image_enhancer) return filter(str.isdigit, text)
def contrast_enhance(self, factor, new_path=None, is_show=False): if self.img is None: img = Image.open(self.path) else: img = self.img img = ImageEnhance.Contrast(img).enhance(factor) if new_path is not None: img.save(new_path) if is_show: img.show(title='contrast') return img
def contrast(func_config): def f(image_config): factor = random.random() * (func_config.max_factor - func_config.min_factor) + func_config.min_factor factor = misc.uniform_sample_from_interval(func_config.min_factor, func_config.max_factor) image_config.image = ImageEnhance.Contrast(image_config.image).enhance(factor) return f
def make_contrast_chg(file_name, path_dir): file_path = path_dir + '/' + file_name img = Image.open('%s' % file_path) ImageEnhance.Contrast(img).enhance(0.8).save(path_dir + '/' + '%02s_ctrt' % file_name.translate(None, '.png') + '.png', "PNG") return
def inkwell(image): # copy = grayscale(image) # enhancer = ImageEnhance.Contrast(copy) # enhancer.enhance(1.1) # enhancer = ImageEnhance.Brightness(copy) # enhancer.enhance(1.1) return image
def nss(image): size = image.size nss = Image.new('RGBA', size, (243, 106, 188, 77)) enhancer = ImageEnhance.Contrast(nss) enhancer.enhance(1.1) enhancer = ImageEnhance.Brightness(nss) enhancer.enhance(1.1) enhancer = ImageEnhance.Color(nss) enhancer.enhance(1.3) copy = image.copy() copy.paste(nss, (0, 0), nss) return copy
def brannan(image): size = image.size brannan = Image.new('RGBA', size, (161, 44, 199, 79)) enhancer = ImageEnhance.Contrast(brannan) enhancer.enhance(1.4) copy = image.copy() copy = sepia(image) copy.paste(brannan, (0, 0), brannan) return copy
def clarendon(image): size = image.size clarendon = Image.new('RGBA', size, (127, 187, 227, 51)) enhancer = ImageEnhance.Contrast(clarendon) enhancer.enhance(1.20) enhancer = ImageEnhance.Color(clarendon) enhancer.enhance(1.35) copy = image.copy() copy.paste(clarendon, (0, 0), clarendon) return copy
def call(self, img): if img is None: raise ValueError('img is None') im_n = img.copy() r = random() contrast_low, contrast_high = 0, self.contrast brightness_low, brightness_high = contrast_high, contrast_high + self.brightness sharpness_low, sharpness_high = brightness_high, brightness_high + self.sharpness color_low, color_high = sharpness_high, sharpness_high + self.color if contrast_low <= r < contrast_high: factor_contrast = randint(5, 10)/10 enhancer = ImageEnhance.Contrast(im_n) im_n = enhancer.enhance(factor_contrast) elif brightness_low <= r < brightness_high: factor_brightness = randint(5, 15)/10 enhancer = ImageEnhance.Brightness(im_n) im_n = enhancer.enhance(factor_brightness) elif sharpness_low <= r < sharpness_high: factor_sharpen = randint(0, 20)/10 enhancer = ImageEnhance.Sharpness(im_n) im_n = enhancer.enhance(factor_sharpen) elif color_low <= r < color_high: factor_color = randint(0, 20)/10 enhancer = ImageEnhance.Color(im_n) im_n = enhancer.enhance(factor_color) else: pass return im_n
def cutimage(url, day): with urllib.request.urlopen(url) as response: r = response.read() menu_img = Image.open(BytesIO(r)) WIDTH = 370 HEIGHT = 123 X = 110 Y = 67 Y = Y + (HEIGHT * day) dailybox = (X, Y, X + WIDTH, Y + HEIGHT) menu = menu_img.crop(dailybox) new_im = Image.new('L', (WIDTH, HEIGHT)) new_im.paste(menu, (0, 0)) enhancer = ImageEnhance.Contrast(new_im) new_im = enhancer.enhance(0.85) new_im = new_im.point(lambda i: i > 90 and 255) new_im = new_im.resize((WIDTH, floor(HEIGHT * 0.56)), Image.BOX) new_im = new_im.convert('1') f = BytesIO() new_im.save(f, format="png", optimize=True, compress_level=9, bits=4) return create_img(f)
def img_preparation(img): img = img.convert('L') sharpness = ImageEnhance.Contrast(img) sharp_img = sharpness.enhance(2.0) two_value_out = sharp_img.point(table, '1') return two_value_out
def randomColor(image): """ ????????? :param image: PIL???image :return: ????????image """ random_factor = np.random.randint(0, 31) / 10. # ???? color_image = ImageEnhance.Color(image).enhance(random_factor) # ???????? random_factor = np.random.randint(10, 21) / 10. # ???? brightness_image = ImageEnhance.Brightness(color_image).enhance(random_factor) # ??????? random_factor = np.random.randint(10, 21) / 10. # ???1? contrast_image = ImageEnhance.Contrast(brightness_image).enhance(random_factor) # ??????? random_factor = np.random.randint(0, 31) / 10. # ???? return ImageEnhance.Sharpness(contrast_image).enhance(random_factor) # ??????
def prepare_image(image_fd): """Returns a PIL image from the given file descriptor. The image is resized in order to filtrate dominant colors and ease k-means computation. The contrast of the image is also enhanced to help find more saturated colors. """ image = Image.open(image_fd) image.thumbnail(THUMBNAIL_SIZE) contrast = ImageEnhance.Contrast(image) image_high_contrast = contrast.enhance(CONTRAST) return image_high_contrast
def code(image): im=Image.open('D:\\Users\\lujunjie\\Desktop\\guoshui\\code.jpg') imgry = im.resize((256,256),Image.BILINEAR).convert('L') # ???????? sharpness = ImageEnhance.Contrast(imgry) # ????? sharp_img = sharpness.enhance(4) sharp_img.save("D:\\Users\\lujunjie\\Desktop\\guoshui\\image_code.jpg") code = image_file_to_string('D:\\Users\\lujunjie\\Desktop\\guoshui\\image_code.jpg') return code
def tesseract(self, img): # keep the data fileName = "tmp_"+int(time.time()+random.randint(1,99999)).__str__()+".jpeg" while os.path.exists( fileName ): fileName = "tmp_"+int(time.time()+random.randint(1,99999)).__str__()+".jpeg" self.tmp_file = fileName with open(self.tmp_file, "w") as oFd: oFd.write(img) # resolve noise try: im = Image.open(self.tmp_file) enhancer = ImageEnhance.Color(im) im = enhancer.enhance(0.0) enhancer = ImageEnhance.Contrast(im) im = enhancer.enhance(3.0) enhancer = ImageEnhance.Brightness(im) im = enhancer.enhance(10.0) enhancer = ImageEnhance.Contrast(im) im = enhancer.enhance(20.0) enhancer = ImageEnhance.Sharpness(im) im = enhancer.enhance(0.0) im.save(self.tmp_file) except Exception as e: pass else: pass # use tesseract imgCode = os.popen("tesseract -l eng -psm 8 {} stdout 2>/dev/null"\ .format(self.tmp_file)).readline()[0:-1] log.debug("Guess Ratio:{}/{}={}%".format(self.guess_hit+1, self.guess_total, \ ((self.guess_hit+1)*100/(self.guess_total)))) os.remove( self.tmp_file ) return imgCode
def get_image(image_path,height,width): """ ???????????????numpy.ndarray image_path:string, height:?????? width:?????? return:numpy.ndarray???tensor """ im = Image.open(image_path).convert('L') #im = ImageEnhance.Contrast(im).enhance(23) b = reshape(im,height,width) return b
def im_contrast(img_path, save_name, ratio): img = Image.open(img_path) img = ImageEnhance.Contrast(img) img = img.enhance(ratio) img.save(save_name, quality=100)
def TF_enhance_contrast(x, p=1.0, target=None): assert len(x.shape) == 3 h, w, nc = x.shape enhancer = ImageEnhance.Contrast(np_to_pil(x)) return pil_to_np(enhancer.enhance(p))
def infer(self, source_obj, embedding_ids, model_dir, save_dir, progress_file): source_provider = InjectDataProvider(source_obj, None) with open(progress_file, 'a') as f: f.write("Start") if isinstance(embedding_ids, int) or len(embedding_ids) == 1: embedding_id = embedding_ids if isinstance(embedding_ids, int) else embedding_ids[0] source_iter = source_provider.get_single_embedding_iter(self.batch_size, embedding_id) else: source_iter = source_provider.get_random_embedding_iter(self.batch_size, embedding_ids) tf.global_variables_initializer().run() saver = tf.train.Saver(var_list=self.retrieve_generator_vars()) self.restore_model(saver, model_dir) def save_imgs(imgs, count): p = os.path.join(save_dir, "inferred_%04d.png" % count) save_concat_images(imgs, img_path=p) # print("generated images saved at %s" % p) def save_sample(imgs, code): p = os.path.join(save_dir, "inferred_%s.png" % code) save_concat_images(imgs, img_path=p) # print("generated images saved at %s" % p) count = 0 batch_buffer = list() for labels, codes, source_imgs in source_iter: fake_imgs = self.generate_fake_samples(source_imgs, labels)[0] for i in range(len(fake_imgs)): # Denormalize image gray_img = np.uint8(fake_imgs[i][:,:,0]*127.5+127.5) pil_img = Image.fromarray(gray_img, 'L') # Apply bilateralFilter cv_img = np.array(pil_img) cv_img = bilateralFilter(cv_img, 5, 10, 10) pil_img = Image.fromarray(cv_img) # Increase contrast enhancer = ImageEnhance.Contrast(pil_img) en_img = enhancer.enhance(1.5) # Normalize image fake_imgs[i][:,:,0] = Image.fromarray(np.array(en_img)/127.5 - 1.) # save_sample(fake_imgs[i], codes[i]) merged_fake_images = merge(scale_back(fake_imgs), [self.batch_size, 1]) batch_buffer.append(merged_fake_images) if len(batch_buffer) == 1: save_sample(batch_buffer, codes[0]) batch_buffer = list() count += 1 if batch_buffer: # last batch save_imgs(batch_buffer, count) with open(progress_file, 'a') as f: f.write("Done")
def crop_image_uniform(src_dir, dst_dir): f = open("399-uniform.txt", "r") if not os.path.exists(dst_dir): os.makedirs(dst_dir) for page in range(1,4): img = Image.open( src_dir + "/" + str(page) +"-uniform.png").convert('L') width, height = img.size cell_width = width/float(cols) cell_height = height/float(rows) header_offset = height/float(rows) * header_ratio width_margin = cell_width * 0.10 height_margin = cell_height * 0.10 for j in range(0,rows): for i in range(0,cols): left = i * cell_width upper = j * cell_height + header_offset right = left + cell_width lower = (j+1) * cell_height center_x = (left + right) / 2 center_y = (upper + lower) / 2 crop_width = right - left - 2*width_margin crop_height = lower - upper - 2*height_margin size = 0 if crop_width > crop_height: size = crop_height/2 else: size = crop_width/2 left = center_x - size; right = center_x + size; upper = center_y - size; lower = center_y + size; code = f.readline() if not code: break else: name = dst_dir + "/uni" + code.strip() + ".png" cropped_image = img.crop((left, upper, right, lower)) cropped_image = cropped_image.resize((128,128), Image.LANCZOS) # Increase constrast enhancer = ImageEnhance.Contrast(cropped_image) cropped_image = enhancer.enhance(1.5) opencv_image = np.array(cropped_image) opencv_image = bilateralFilter(opencv_image, 9, 30, 30) cropped_image = Image.fromarray(opencv_image) cropped_image.save(name) print("Processed uniform page " + str(page))
def ModifyImg(self,img_name): global val_img val_img+=1 if val_img <= 1: print('??????????----------') if os.path.isdir(Modif): pass else: mkdir = os.makedirs(Modif) print('????????????????????----------') print('???????????????????->'+Modif) else: pass img = Image.open(img_name) img = img.filter(ImageFilter.MedianFilter()) enhancer = ImageEnhance.Contrast(img) img = enhancer.enhance(2) img = img.convert('1') width, height = img.size data = [] for i in range(height): tmp=[] for j in range(width): if(img.getpixel((j,i)) == 255 ): tmp.append(1) else: tmp.append(0) data.append(tmp) img2 = Image.new("P",img.size, 255) for y in range(height): for a in range(len(data[y])): o = y+1 t = y+2 #s = y+3 z = a+1 x = a+2 try: if data[o][a] == 0 and data[t][a] == 0 and data[y][z] == 0 and data[y][x] == 0:#and data[s][a] == 0 img2.putpixel((a,y),1) img2.save(Modif+str(val_img)+'.png') except: pass img2_path = Modif+str(val_img)+'.png' image = Image.open(img2_path) image = image.convert("L") self.clearNoise(image,53,4,8) image.save(img2_path) image.show() self.ImgCutting(img2_path)
def online_rotate_picture(image): """ ?????, ?????? ???????????????? :param image: :return: """ # ?????????????????????????? box = image.getbbox() width = box[2] - box[0] height = box[3] - box[1] # print('?????{}??{}??{}'.format(box, width, height)) # ??????????????????? region = image.crop((box[0], box[1], box[2], box[1] + 1)) box2 = region.getbbox() mid = width / 2 if box2[0] < mid < box2[2]: # ???????? ????? return image adjacent = max(box2[0], width - box2[2]) # ?? # print('?????{}???{}'.format(box2, adjacent)) # ??????????????????? region = image.crop((box[0], box[1], box[0] + 1, box[3])) box3 = region.getbbox() opposite = max(box3[1], height - box3[3]) # ?? # print('?????{}???{}'.format(box3, opposite)) import math angle = math.atan(opposite / adjacent) / math.pi * 180 if box2[0] > mid: # ????????????????????????? angle = - angle # print('??????{}'.format(int(angle))) # ?? size = image.size ret = image.resize((size[0] * 2, size[1] * 2), Image.ANTIALIAS) # ?? ret = ret.rotate(angle) # ????????????????? from PIL import ImageEnhance ret = ImageEnhance.Contrast(ret) ret = ret.enhance(2) # ?? ret = ret.crop(ret.getbbox()) # box = image.getbbox() # width = box[2] - box[0] # height = box[3] - box[1] # print('?????{}??{}??{}'.format(box, width, height)) return ret
def main(): import argparse parser = argparse.ArgumentParser(description="Combine your QR code with custom picture") parser.add_argument("image") parser.add_argument("text", help="QRcode Text.") parser.add_argument("-o", "--output", help="Name of output file.") parser.add_argument("-v", "--version", type=int, help="QR version.In range of [1-40]") parser.add_argument("-e", "--errorcorrect", choices={"L","M","Q","H"}, help="Error correct") parser.add_argument("-b", "--brightness", type=float, help="Brightness enhance") parser.add_argument("-c", "--contrast", type=float, help="Contrast enhance") parser.add_argument("-C", "--colourful", action="store_true",help="colourful mode") parser.add_argument("-r", "--rgba", nargs=4, metavar=('R','G','B','A'),type = int, help="color to replace black") parser.add_argument("-p", "--pixelate", action="store_true",help="pixelate") args = parser.parse_args() img = args.image txt = args.text output = args.output if args.output else 'qr.png' ec = qrcode.constants.ERROR_CORRECT_H if args.errorcorrect: ec_raw = args.errorcorrect if ec_raw == 'L': ec = qrcode.constants.ERROR_CORRECT_L if ec_raw == 'M': ec = qrcode.constants.ERROR_CORRECT_M if ec_raw == 'Q': ec = qrcode.constants.ERROR_CORRECT_Q ver = 5 if args.version: if args.version >= 1 and args.version <= 40: ver = args.version cont = args.contrast if args.contrast else 1.0 bri = args.brightness if args.brightness else 1.0 colr = True if args.colourful else False pixelate = True if args.pixelate else False if colr : if args.rgba: rgba = tuple(args.rgba) else: rgba = (0,0,0,255) else: rgba = (0,0,0,255) frames = produce(txt,img,ver,ec,bri, cont ,colourful = colr,rgba=rgba,pixelate = pixelate) if len(frames) == 1 or output.upper()[-3:] != "GIF": frames[0].save(output) elif len(frames) > 1: frames[0].save(output,save_all=True,append_images=frames[1:],duration=100,optimize=True)
