【摄影后期技巧】连拍多张图像中快速找到最清晰的图像—

【摄影后期技巧】连拍多张图像中快速找到最清晰的图像——Python代码实现

news2024/9/21 18:55:48

手持相机高速连拍过程，当快门速度不够高时不可避免出现模糊帧，通过肉眼去从多张连拍图像中找到最清晰的帧是比较费事的，可通过代码自动去计算最清晰的图像，省去挑选图像的麻烦事，同时也可以将模糊图像剔除掉，提高后期PS堆栈的效果

import os
from PIL import Image
import numpy as np

def CLIP(value, down, top):
    if value <= down:
        return down
    if value >= top:
        return top
    return value

def check_roi_region(roi_region, w, h):
    safe_roi_region = [0, w-2, 0, h-2]
    if (roi_region[0] == 0 and roi_region[1] == 0 and roi_region[2] == 0 and roi_region[3] == 0):
        return safe_roi_region
    if (roi_region[1] < roi_region[0]) or (roi_region[3] < roi_region[2]):
        print("check your roi_region!")
        return safe_roi_region

    roi_region[0] = CLIP(roi_region[0], 0, w-2)
    roi_region[1] = CLIP(roi_region[1], 0, w - 2)
    roi_region[2] = CLIP(roi_region[2], 0, h - 2)
    roi_region[3] = CLIP(roi_region[3], 0, h - 2)
    return roi_region

def cal_resolution(img_gray, roi_region):
    resolution = 0
    w, h = img_gray.shape
    start_x, end_x, start_y, end_y = check_roi_region(roi_region, w, h)
    dx = np.sum(np.abs(np.gradient(img_gray[start_x:end_x, start_y:end_y], axis=1)))  # 水平方向梯度
    dy = np.sum(np.gradient(img_gray[start_x:end_x, start_y:end_y], axis=0))  # 垂直方向梯度
    resolution = dx + dy
    return resolution

def main():
    imgs_dir = r'E:\MyCode\python_code\data\case3'
    roi_region = [0, 0, 0, 0]    #可设置计算清晰度的矩形区域，如只计算人脸区域，默认全图计算

    imgs_names = os.listdir(imgs_dir)
    imgs_names = [file for file in imgs_names if file.lower().endswith('.jpg')]
    print("图像数量：", len(imgs_names))

    count = 1
    img_resolution_list = []
    for img in imgs_names:
        img_path = os.path.join(imgs_dir, img)
        img_src = Image.open(img_path)
        img_gray = np.array(img_src.convert('L'))
        img_resolution = cal_resolution(img_gray, roi_region)
        img_resolution_list.append(img_resolution)
        print(count, img_path, img_resolution)
        count += 1

    imgs_names_and_resolution_list = list(zip(imgs_names, img_resolution_list))
    sorted_resolution_list = sorted(imgs_names_and_resolution_list, key=lambda x: x[1], reverse=True)
    print("=========以下按清晰度从高到低排序=========")
    for idx, img in enumerate(sorted_resolution_list):
        print(idx + 1, img)


if __name__ == "__main__":
    main()

=========以下按清晰度从高到低排序=========
1 ('DSC_3623.JPG', 33861616.5)
2 ('DSC_3605.JPG', 32694941.5)
3 ('DSC_3593.JPG', 32577916.5)
4 ('DSC_3601.JPG', 31280211.0)
5 ('DSC_3592.JPG', 30576425.5)
6 ('DSC_3599.JPG', 30550129.5)
7 ('DSC_3607.JPG', 30258823.5)
8 ('DSC_3574.JPG', 29138570.0)
9 ('DSC_3624.JPG', 29127739.5)
10 ('DSC_3578.JPG', 29041243.5)
11 ('DSC_3619.JPG', 28843627.0)
12 ('DSC_3590.JPG', 28563339.0)
13 ('DSC_3618.JPG', 28483760.5)
14 ('DSC_3606.JPG', 28448455.0)
15 ('DSC_3573.JPG', 27737165.0)
...............................
50 ('DSC_3582.JPG', 19952055.5)
51 ('DSC_3616.JPG', 18890835.5)
52 ('DSC_3609.JPG', 18709554.5)
53 ('DSC_3632.JPG', 16350545.5)
54 ('DSC_3631.JPG', 15735590.0)
55 ('DSC_3584.JPG', 14930016.5)
56 ('DSC_3621.JPG', 14896296.5)
57 ('DSC_3586.JPG', 14681760.5)
58 ('DSC_3610.JPG', 14539433.5)
59 ('DSC_3612.JPG', 14300990.5)
60 ('DSC_3611.JPG', 14108023.5)
61 ('DSC_3585.JPG', 13996736.5)