from PIL import Image, ImageFont, ImageDraw, ImageOps from io import BytesIO 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): import cv2 # 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 bytes_to_pil(image_bytes): image = Image.open(BytesIO(image_bytes)) image = image.convert('RGB') return image 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 = bytes_to_pil(image_bytes) 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)