Excel为数据绘制拆线图,并将均值线叠加在图上,以及整个过程的区域录屏python脚本
- 1.演示动画
- A.视频
- B.gif动画
- 2.跟踪鼠标区域的录屏脚本
Excel中有一组数据,希望画出曲线,并且能把均值线也绘制在图上,以下动画演示了整个过程,并且提供了区域录屏脚本,原理如下:
为节约空间,避免剪辑,只记录有效区域【仅记录鼠标区域且图像变化的图片】
1.演示动画
A.视频
Excel为数据绘制拆线图,并将均值线叠加在图上
B.gif动画
2.跟踪鼠标区域的录屏脚本
import cv2
import numpy as np
import mss
import time
import threading
import pyautogui
import datetime
from skimage.metrics import structural_similarity as ssim
from pynput import mouse
def compute_ssim(imageA, imageB):
"""计算两幅图像的结构相似性指数(SSIM)"""
grayA = cv2.cvtColor(imageA, cv2.COLOR_BGR2GRAY)
grayB = cv2.cvtColor(imageB, cv2.COLOR_BGR2GRAY)
(score, diff) = ssim(grayA, grayB, full=True)
return score
def resize_and_pad(image, size=(640, 640)):
"""等比缩放并填充图像"""
h, w = image.shape[:2]
scale = min(size[0] / w, size[1] / h)
new_w, new_h = int(w * scale), int(h * scale)
resized_image = cv2.resize(image, (new_w, new_h))
# 创建黑色背景
top = (size[1] - new_h) // 2
bottom = size[1] - new_h - top
left = (size[0] - new_w) // 2
right = size[0] - new_w - left
padded_image = cv2.copyMakeBorder(resized_image, top, bottom, left, right, cv2.BORDER_CONSTANT, value=[0, 0, 0])
return padded_image
is_mouse_pressed=False
def on_click(x, y, button, pressed):
global is_mouse_pressed
is_mouse_pressed = pressed
def capture_screen(stop_event):
layout_w=720
layout_h=1280
mouse_listener = mouse.Listener(on_click=on_click)
mouse_listener.start()
with mss.mss() as sct:
# 初始化第一帧
monitor = sct.monitors[1]
print(monitor)
frame1 = None
screen_width = monitor["width"]
screen_height = monitor["height"]
fourcc = cv2.VideoWriter_fourcc(*'XVID')
out = cv2.VideoWriter('output.avi', fourcc, 3.0, (layout_w, layout_h))
area=None
while not stop_event.is_set():
mouse_x, mouse_y = pyautogui.position()
if area:
if mouse_x<area['left'] or mouse_x>area['left']+layout_w or mouse_y<area['top'] or mouse_y>area['top']+layout_h:
area=None
if area is None and is_mouse_pressed:
# 计算截取区域,以鼠标为中心640x640,同时进行边界检查
left = max(0, min(screen_width - layout_w, mouse_x - layout_w // 2))
top = max(0, min(screen_height - layout_h, mouse_y - layout_h // 2))
area = {'top': top, 'left': left, 'width': layout_w, 'height': layout_h}
if area:
frame2 = np.array(sct.grab(area))
frame2 = cv2.cvtColor(frame2, cv2.COLOR_BGRA2BGR)
# 在 frame2 上绘制一个小圆点标记鼠标位置
relative_mouse_x = mouse_x - area['left']
relative_mouse_y = mouse_y - area['top']
cv2.circle(frame2, (relative_mouse_x, relative_mouse_y), 5, (0, 0, 255), -1) # 红色小圆点
frame2=resize_and_pad(frame2,(layout_w,layout_h))
if frame1 is None:
frame1 = frame2.copy()
continue
score = compute_ssim(frame1, frame2)
if score<1.0:
out.write(frame2)
frame1 = frame2.copy()
# 适量的延时,防止过高的CPU使用率
time.sleep(0.1)
out.release()
if __name__ == '__main__':
stop_event = threading.Event()
# 启动屏幕捕捉的线程
capture_thread = threading.Thread(target=capture_screen, args=(stop_event,))
capture_thread.start()
# 等待用户输入'q'以停止捕捉
while True:
if input().strip().lower() == 'q':
stop_event.set()
break
# 等待屏幕捕捉线程结束
capture_thread.join()
print("捕获已结束并退出。")
from moviepy.editor import VideoFileClip
# 定义视频文件路径和输出GIF文件路径
input_video_path = 'output.avi'
output_gif_path = 'output.gif'
# 加载视频文件
clip = VideoFileClip(input_video_path)
clip = clip.subclip(3, -2)
clip = clip.resize(0.4)
# 将视频剪辑转换为GIF
clip.write_gif(output_gif_path, fps=2)
print(f"GIF文件保存到 {output_gif_path}")