import os
import random
import string

# 讀取face.txt文件中的URL
with open('face.txt', 'r') as f:
    urls = f.read().splitlines()

# 生成額外URL的函數(shù)
def generate_extra_urls(base_urls, num_extra):
    extra_urls = []
    for _ in range(num_extra):
        base_url = random.choice(base_urls)
        # 這里我們簡單地通過添加隨機(jī)字符串來模擬新的URL
        # 在實(shí)際應(yīng)用中，你可能需要更復(fù)雜的策略來生成有意義的URL
        random_str = ''.join(random.choices(string.ascii_uppercase + string.digits, k=10))
        extra_url = f"{base_url}?extra={random_str}"
        extra_urls.append(extra_url)
    return extra_urls

# 生成200個(gè)額外的URL
extra_urls = generate_extra_urls(urls, 200)

# 將原始URL和額外生成的URL合并
all_urls = urls + extra_urls

# 將所有URL寫入新的文件
with open('all_faces.txt', 'w') as f:
    for url in all_urls:
        f.write(f"{url}\n")

print("數(shù)據(jù)增強(qiáng)完成，所有URL已寫入all_faces.txt文件。")

import os
import requests
from PIL import Image, ImageOps, ImageEnhance
import numpy as np
import random

# 下載圖像的函數(shù)
def download_image(url, save_path):
    response = requests.get(url, stream=True)
    if response.status_code == 200:
        with open(save_path, 'wb') as f:
            for chunk in response:
                f.write(chunk)
    else:
        print(f"Failed to download image from {url}")

# 圖像增強(qiáng)的函數(shù)
def enhance_image(image_path, output_dir):
    # 讀取圖像
    image = Image.open(image_path)
    
    # 幾何變換示例：隨機(jī)翻轉(zhuǎn)
    if random.choice([True, False]):
        image = ImageOps.flip(image)
    
    # 像素變換示例：添加噪聲
    if random.choice([True, False]):
        noise = np.random.normal(0, 10, image.size)
        noisy_image = Image.fromarray(np.clip(image + noise, 0, 255).astype(np.uint8))
        image = noisy_image
    
    # 保存增強(qiáng)后的圖像
    output_path = os.path.join(output_dir, f"enhanced_{os.path.basename(image_path)}")
    image.save(output_path)

# 讀取face.txt文件中的URL
with open('face.txt', 'r') as f:
    urls = f.read().splitlines()

# 下載并增強(qiáng)圖像的目錄
download_dir = 'downloaded_images'
enhanced_dir = 'enhanced_images'

# 如果目錄不存在，則創(chuàng)建它們
if not os.path.exists(download_dir):
    os.makedirs(download_dir)
if not os.path.exists(enhanced_dir):
    os.makedirs(enhanced_dir)

# 下載并增強(qiáng)圖像
for url in urls:
    image_path = os.path.join(download_dir, f"face_{os.path.basename(url.split('/')[-1])}")
    download_image(url, image_path)
    enhance_image(image_path, enhanced_dir)

print("數(shù)據(jù)增強(qiáng)完成，增強(qiáng)后的圖像已保存在", enhanced_dir)

import os
import requests
from PIL import Image
import imgaug as ia
from imgaug import augmenters as iaa

# 下載圖像的函數(shù)
def download_image(url, save_path):
    response = requests.get(url, stream=True)
    if response.status_code == 200:
        with open(save_path, 'wb') as f:
            for chunk in response:
                f.write(chunk)
    else:
        print(f"Failed to download image from {url}")

# 定義數(shù)據(jù)增強(qiáng)序列
def create_augmentation_seq():
    seq = iaa.Sequential([
        iaa.Fliplr(0.5),  # 水平翻轉(zhuǎn)，50%的概率
        iaa.Flipud(0.5),  # 垂直翻轉(zhuǎn)，50%的概率
        iaa.Affine(
            rotate=(-20, 20),  # 隨機(jī)旋轉(zhuǎn)，范圍在-20到20度之間
            scale=(0.8, 1.2),  # 隨機(jī)縮放，范圍在0.8到1.2倍之間
            translate_percent={"x": (-0.1, 0.1), "y": (-0.1, 0.1)},  # 隨機(jī)平移，范圍在-10%到10%之間
            mode="constant",  # 使用常數(shù)填充新的像素
            cval=(0, 255)    # 填充像素的值范圍
        ),
        iaa.AdditiveGaussianNoise(loc=0, scale=(0.0, 0.05*255), per_channel=0.5),  # 添加高斯噪聲
        iaa.ContrastNormalization((0.7, 1.3)),  # 對(duì)比度歸一化
    ], random_order=True)  # 每次應(yīng)用增強(qiáng)時(shí)的順序是隨機(jī)的
    return seq

# 主程序
def main():
    # 讀取face.txt文件中的URL
    with open('face.txt', 'r') as f:
        urls = f.read().splitlines()

    # 下載圖像的目錄
    download_dir = 'downloaded_images'
    # 增強(qiáng)后圖像的目錄
    augmented_dir = 'augmented_images'

    # 創(chuàng)建目錄
    if not os.path.exists(download_dir):
        os.makedirs(download_dir)
    if not os.path.exists(augmented_dir):
        os.makedirs(augmented_dir)

    # 創(chuàng)建數(shù)據(jù)增強(qiáng)序列
    seq = create_augmentation_seq()

    # 下載并增強(qiáng)圖像
    for idx, url in enumerate(urls):
        image_path = os.path.join(download_dir, f"face_{idx}.jpg")
        download_image(url, image_path)

        # 讀取圖像
        image = Image.open(image_path)
        # 將PIL圖像轉(zhuǎn)換為numpy數(shù)組
        image_array = np.array(image)

        # 應(yīng)用數(shù)據(jù)增強(qiáng)
        augmented_images = seq(images=[image_array])

        # 保存增強(qiáng)后的圖像
        for i, aug_image in enumerate(augmented_images):
            aug_image_path = os.path.join(augmented_dir, f"face_{idx}_aug_{i}.jpg")
            Image.fromarray(aug_image).save(aug_image_path)

    print("數(shù)據(jù)增強(qiáng)完成，增強(qiáng)后的圖像已保存在", augmented_dir)

# 運(yùn)行主程序
if __name__ == "__main__":
    main()