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crop_image.py
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from PIL import Image, ImageFont, ImageDraw, ImageOps
from io import BytesIO
import cv2
import numpy as np
import os
current_path = os.getcwd()
validate_path = os.path.join(current_path,'img_2_val')#要验证的图片暂存
save_path = os.path.join(current_path,'img_saved')#存放历史图片，留作做数据集以待标记
save_pass_path = os.path.join(save_path,'img_pass')#校验失败的图片，可能是轨迹有误，不一定是分类错误
save_fail_path = os.path.join(save_path,'img_fail')#校验成功的图片，但有可能有个别分类错误
os.makedirs(validate_path,exist_ok=True)
os.makedirs(save_path,exist_ok=True)
os.makedirs(save_pass_path,exist_ok=True)
os.makedirs(save_fail_path,exist_ok=True)
def draw_points_on_image(bg_image, answer):
# 将背景图片转换为OpenCV格式
bg_image_cv = cv2.imdecode(np.frombuffer(bg_image, dtype=np.uint8), cv2.IMREAD_COLOR)
# 定义九宫格的大小和偏移量
grid_width = 100
grid_height = 86
offset_x = 45
offset_y = 38
for i, (row, col) in enumerate(answer):
x = offset_x + (col-1) * grid_width
y = offset_y + (row-1) * grid_height
cv2.circle(bg_image_cv, (x, y), 10, (0, 0, 255), -1)
cv2.imwrite('./img_2_val/predicted.jpg', bg_image_cv)#推理结果
def convert_png_to_jpg(png_bytes: bytes) -> bytes:
# 将传入的 bytes 转换为图像对象
png_image = Image.open(BytesIO(png_bytes))
# 创建一个 BytesIO 对象，用于存储输出的 JPG 数据
output_bytes = BytesIO()
# 检查图像是否具有透明度通道 (RGBA)
if png_image.mode == 'RGBA':
# 创建白色背景
white_bg = Image.new("RGB", png_image.size, (255, 255, 255))
# 将 PNG 图像粘贴到白色背景上，透明部分用白色填充
white_bg.paste(png_image, (0, 0), png_image)
jpg_image = white_bg
else:
# 如果图像没有透明度，直接转换为 RGB 模式
jpg_image = png_image.convert("RGB")
# 将转换后的图像保存为 JPG 格式到 BytesIO 对象
jpg_image.save(output_bytes, format="JPEG")
# 返回保存后的 JPG 图像的 bytes
return output_bytes.getvalue()
def crop_image(image_bytes, coordinates):
img = Image.open(BytesIO(image_bytes))
width, height = img.size
grid_width = width // 3
grid_height = height // 3
cropped_images = []
for coord in coordinates:
y, x = coord
left = (x - 1) * grid_width
upper = (y - 1) * grid_height
right = left + grid_width
lower = upper + grid_height
box = (left, upper, right, lower)
cropped_img = img.crop(box)
cropped_images.append(cropped_img)
return cropped_images
def crop_image_v3(image_bytes):
coordinates = [
[[0, 0], [112, 112]],
[[116, 0], [228, 112]],
[[232, 0], [344, 112]],#第一行
[[0, 116], [112, 228]],
[[116, 116], [228, 228]],
[[232, 116], [344, 228]],#第二行
[[0, 232], [112, 344]],
[[116, 232], [228, 344]],
[[232, 232], [344, 344]],#第三行
[[2, 344], [42, 384]] #要验证的
]
image = Image.open(BytesIO(image_bytes))
image = Image.fromarray(cv2.cvtColor(np.array(image), cv2.COLOR_RGBA2RGB))
imageNew = Image.new('RGB', (300,261),(0,0,0))
images = []
for i, (start_point, end_point) in enumerate(coordinates):
x1, y1 = start_point
x2, y2 = end_point
# 切割图像
cropped_image = image.crop((x1, y1, x2, y2))
images.append(cropped_image)
# 保存切割后的图像
output_path = os.path.join(validate_path,f'cropped_{i}.jpg')
cropped_image.save(output_path)
for i in range(3):
imageNew.paste(images[i].resize((100,86)), (i*100, 0, (i+1)*100, 86))
imageNew.paste(images[i+3].resize((100,86)), (i*100, 86, (i+1)*100, 172))
imageNew.paste(images[i+6].resize((100,86)), (i*100,172, (i+1)*100, 258))
imageNew.save(os.path.join(validate_path,f'nine.jpg') )
if __name__ == "__main__":
# v4测试代码
# os.makedirs(os.path.join(current_path,'image_test'),exist_ok=True)
# # 切割顺序，这里是从左到右，从上到下[x,y]
# coordinates = [
# [1, 1],
# [1, 2],
# [1, 3],
# [2, 1],
# [2, 2],
# [2, 3],
# [3, 1],
# [3, 2],
# [3, 3],
# ]
# with open("./image_test/bg.jpg", "rb") as rb:
# bg_img = rb.read()
# cropped_images = crop_image(bg_img, coordinates)
# # 一个个保存下来
# for j, img_crop in enumerate(cropped_images):
# img_crop.save(f"./image_test/bg{j}.jpg")
# # 图标格式转换
# with open("./image_test/icon.png", "rb") as rb:
# icon_img = rb.read()
# icon_img_jpg = convert_png_to_jpg(icon_img)
# with open("./image_test/icon.jpg", "wb") as wb:
# wb.write(icon_img_jpg)
# V3测试代码
pic = "img_saved/7fe559a85bac4c03bc6ea7b2e85325bf.jpg"
print("推理图片为：",pic)
with open(pic, "rb") as f:
img = f.read()
crop_image_v3(img)