feat design 预处理新增padding 处理 使图片不要完全贴边
fix
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@@ -60,6 +60,7 @@ class DesignPreprocessing:
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def bounding_box(self, image_list):
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for item in image_list:
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image = item['image_obj']
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height, width = image.shape[:2]
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# 使用Canny边缘检测来检测物体的轮廓
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edges = cv2.Canny(image, 50, 150)
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# 查找轮廓
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@@ -83,16 +84,25 @@ class DesignPreprocessing:
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if len(contours) > 0:
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cropped_image = image[y_min:y_max, x_min:x_max]
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item['obj'] = cropped_image # 新shape图像
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# 取消直接覆盖,新增size判断
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# try:
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# # 覆盖到minio
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# image_bytes = cv2.imencode(".jpg", cropped_image)[1].tobytes()
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# self.minio_client.put_object(item['image_url'].split("/", 1)[0], item['image_url'].split("/", 1)[1], io.BytesIO(image_bytes), len(image_bytes), content_type="image/jpeg", )
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# print(f"Object '{item['image_url'].split('/', 1)[1]}' overwritten successfully.")
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# except ResponseError as err:
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# print(f"Error: {err}")
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else:
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item['obj'] = image
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padding_top = max(20 - y_min, 0)
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padding_bottom = max(20 - (height - y_max), 0)
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padding_left = max(20 - x_min, 0)
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padding_right = max(20 - (width - x_max), 0)
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# 添加padding
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padded_image = cv2.copyMakeBorder(
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image,
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padding_top,
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padding_bottom,
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padding_left,
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padding_right,
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cv2.BORDER_CONSTANT,
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value=(255, 255, 255) # 你可以选择填充颜色,例如黑色
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)
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item['obj'] = padded_image
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return image_list
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def super_resolution(self, image_list):
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@@ -334,7 +344,7 @@ class DesignPreprocessing:
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]
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try:
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# connections.connect(alias=MILVUS_ALIAS, host=MILVUS_DB_HOST, port=MILVUS_PORT)
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start_time = time.time()
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# start_time = time.time()
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# collection = Collection(MILVUS_TABLE_KEYPOINT) # Get an existing collection.
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# mr = collection.upsert(data)
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# logging.info(f"save keypoint time : {time.time() - start_time}")
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@@ -348,9 +358,9 @@ if __name__ == '__main__':
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data = {
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"sketches": [
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{
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"image_category": "dress",
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"image_id": "107903",
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"image_url": "aida-sys-image/images/female/dress/0628000000.jpg"
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"image_category": "blouse",
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"image_id": "123123123",
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"image_url": "test/0628000198.jpg"
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}
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]
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}
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