怎么使用Python代码批量做素描图
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1. 流程分析
对于上面的流程来说是非常简单的,接下来我们来看看具体的实现。
2. 具体实现
安装所需要的库:
pip install opencv-python
导入所需要的库:
import cv2
编写主体代码也是非常的简单的,代码如下:
import cv2 SRC = "images/image_1.jpg" image_rgb = cv2.imread(SRC) image_gray = cv2.cvtColor(image_rgb, cv2.COLOR_BGR2GRAY) image_blur = cv2.GaussianBlur(image_gray, ksize=(21, 21), sigmaX=0, sigmaY=0) image_blend = cv2.divide(image_gray, image_blur, scale=255) cv2.imwrite("result.jpg", image_blend)
那上面的代码其实并不难,那接下来为了让小伙伴们能更好的理解,我编写了如下代码:
""" project = "Code", file_name = "study.py", author = "AI悦创" time = "2020/5/19 8:35", product_name = PyCharm, 公众号:AI悦创 code is far away from bugs with the god animal protecting I love animals. They taste delicious. """ import cv2 # 原图路径 SRC = "images/image_1.jpg" # 读取图片 image_rgb = cv2.imread(SRC) # cv2.imshow("rgb", image_rgb) # 原图 # cv2.waitKey(0) # exit() image_gray = cv2.cvtColor(image_rgb, cv2.COLOR_BGR2GRAY) # cv2.imshow("gray", image_gray) # 灰度图 # cv2.waitKey(0) # exit() image_bulr = cv2.GaussianBlur(image_gray, ksize=(21, 21), sigmaX=0, sigmaY=0) cv2.imshow("image_blur", image_bulr) # 高斯虚化 cv2.waitKey(0) exit() # divide: 提取两张差别较大的线条和内容 image_blend = cv2.divide(image_gray, image_bulr, scale=255) # cv2.imshow("image_blend", image_blend) # 素描 cv2.waitKey(0) # cv2.imwrite("result1.jpg", image_blend)
那上面的代码,我们是在原有的基础上添加了,一些实时展示的代码,来方便同学们理解。
其实有同学会问,我用软件不就可以直接生成素描图吗?
那程序的好处是什么?
程序的好处就是如果你的图片量多的话,这个时候使用程序批量生成也是非常方便高效的。
这样我们的就完成,把小姐姐的图片变成了素描,skr~。
3. 百度图片爬虫+生成素描图
不过,这还不是我们的海量图片,为了达到海量这个词呢,我写了一个百度图片爬虫,不过本文不是教如何写爬虫代码的,这里我就直接放出爬虫代码,符和软件工程规范:
# Crawler.Spider.py import re import os import time import collections from collections import namedtuple import requests from concurrent import futures from tqdm import tqdm from enum import Enum BASE_URL = "https://image.baidu.com/search/acjson?tn=resultjson_com&ipn=rj&ct=201326592&is=&fp=result&queryWord={keyword}&cl=2&lm=-1&ie=utf-8&oe=utf-8&adpicid=&st=-1&z=&ic=&hd=&latest=©right=&word={keyword}&s=&se=&tab=&width=&height=&face=0&istype=2&qc=&nc=1&fr=&expermode=&force=&pn={page}&rn=30&gsm=&1568638554041=" HEADERS = { "Referer": "http://image.baidu.com/search/index?tn=baiduimage&ipn=r&ct=201326592&cl=2&lm=-1&st=-1&fr=&sf=1&fmq=1567133149621_R&pv=&ic=0&nc=1&z=0&hd=0&latest=0©right=0&se=1&showtab=0&fb=0&width=&height=&face=0&istype=2&ie=utf-8&sid=&word=%E5%A3%81%E7%BA%B8", "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36", "X-Requested-With": "XMLHttpRequest", } class BaiDuSpider: def __init__(self, max_works, images_type): self.max_works = max_works self.HTTPStatus = Enum("Status", ["ok", "not_found", "error"]) self.result = namedtuple("Result", "status data") self.session = requests.session() self.img_type = images_type self.img_num = None self.headers = HEADERS self.index = 1 def get_img(self, img_url): res = self.session.get(img_url) if res.status_code != 200: res.raise_for_status() return res.content def download_one(self, img_url, verbose): try: image = self.get_img(img_url) except requests.exceptions.HTTPError as e: res = e.response if res.status_code == 404: status = self.HTTPStatus.not_found msg = "not_found" else: raise else: self.save_img(self.img_type, image) status = self.HTTPStatus.ok msg = "ok" if verbose: print(img_url, msg) return self.result(status, msg) def get_img_url(self): urls = [BASE_URL.format(keyword=self.img_type, page=page) for page in self.img_num] for url in urls: res = self.session.get(url, headers=self.headers) if res.status_code == 200: img_list = re.findall(r""thumbURL":"(.*?)"", res.text) # 返回出图片地址,配合其他函数运行 yield {img_url for img_url in img_list} elif res.status_code == 404: print("-----访问失败,找不到资源-----") yield None elif res.status_code == 403: print("*****访问失败,服务器拒绝访问*****") yield None else: print(">>> 网络连接失败 <<<") yield None def download_many(self, img_url_set, verbose=False): if img_url_set: counter = collections.Counter() with futures.ThreadPoolExecutor(self.max_works) as executor: to_do_map = {} for img in img_url_set: future = executor.submit(self.download_one, img, verbose) to_do_map[future] = img done_iter = futures.as_completed(to_do_map) if not verbose: done_iter = tqdm(done_iter, total=len(img_url_set)) for future in done_iter: try: res = future.result() except requests.exceptions.HTTPError as e: error_msg = "HTTP error {res.status_code} - {res.reason}" error_msg = error_msg.format(res=e.response) except requests.exceptions.ConnectionError: error_msg = "ConnectionError error" else: error_msg = "" status = res.status if error_msg: status = self.HTTPStatus.error counter[status] += 1 if verbose and error_msg: img = to_do_map[future] print("***Error for {} : {}".format(img, error_msg)) return counter else: pass def save_img(self, img_type, image): with open("{}/{}.jpg".format(img_type, self.index), "wb") as f: f.write(image) self.index += 1 def what_want2download(self): # self.img_type = input("请输入你想下载的图片类型,什么都可以哦~ >>> ") try: os.mkdir(self.img_type) except FileExistsError: pass img_num = input("请输入要下载的数量(1位数代表30张,列如输入1就是下载30张,2就是60张):>>> ") while True: if img_num.isdigit(): img_num = int(img_num) * 30 self.img_num = range(30, img_num + 1, 30) break else: img_num = input("输入错误,请重新输入要下载的数量>>> ") def main(self): # 获取图片类型和下载的数量 total_counter = {} self.what_want2download() for img_url_set in self.get_img_url(): if img_url_set: counter = self.download_many(img_url_set, False) for key in counter: if key in total_counter: total_counter[key] += counter[key] else: total_counter[key] = counter[key] else: # 可以为其添加报错功能 pass time.sleep(.5) return total_counter if __name__ == "__main__": max_works = 20 bd_spider = BaiDuSpider(max_works) print(bd_spider.main())
# Sketch_the_generated_code.py import cv2 def drawing(src, id=None): image_rgb = cv2.imread(src) image_gray = cv2.cvtColor(image_rgb, cv2.COLOR_BGR2GRAY) image_blur = cv2.GaussianBlur(image_gray, ksize=(21, 21), sigmaX=0, sigmaY=0) image_blend = cv2.divide(image_gray, image_blur, scale=255) cv2.imwrite(f"Drawing_images/result-{id}.jpg", image_blend)
# image_list.image_list_path.py import os from natsort import natsorted IMAGES_LIST = [] def image_list(path): global IMAGES_LIST for root, dirs, files in os.walk(path): # 按文件名排序 # files.sort() files = natsorted(files) # 遍历所有文件 for file in files: # 如果后缀名为 .jpg if os.path.splitext(file)[1] == ".jpg": # 拼接成完整路径 # print(file) filePath = os.path.join(root, file) print(filePath) # 添加到数组 IMAGES_LIST.append(filePath) return IMAGES_LIST
# main.py import time from Sketch_the_generated_code import drawing from Crawler.Spider import BaiDuSpider from image_list.image_list_path import image_list import os MAX_WORDS = 20 if __name__ == "__main__": # now_path = os.getcwd() # img_type = "ai" img_type = input("请输入你想下载的图片类型,什么都可以哦~ >>> ") bd_spider = BaiDuSpider(MAX_WORDS, img_type) print(bd_spider.main()) time.sleep(10) # 这里设置睡眠时间,让有足够的时间去添加,这样读取就,去掉或者太短会报错,所以 for index, path in enumerate(image_list(img_type)): drawing(src = path, id = index)
所以最终的目录结构如下所示:
C:. │ main.py │ Sketch_the_generated_code.py │ ├─Crawler │ │ Spider.py │ │ │ └─__pycache__ │ Spider.cpython-37.pyc │ ├─drawing │ │ result.jpg │ │ result1.jpg │ │ Sketch_the_generated_code.py │ │ study.py │ │ │ ├─images │ │ image_1.jpg │ │ │ └─__pycache__ │ Sketch_the_generated_code.cpython-37.pyc │ ├─Drawing_images ├─image_list │ │ image_list_path.py │ │ │ └─__pycache__ │ image_list_path.cpython-37.pyc │ └─__pycache__ Sketch_the_generated_code.cpython-37.pyc
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文章名称:怎么使用Python代码批量做素描图
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