deep_learning/HivisionIDPhotos
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feat: api support whitening (#257)

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汉图-汪钧剑 2025-07-11 01:12:45 +08:00 committed by GitHub
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commit 6b46f0f66b
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1 changed files with 6 additions and 2 deletions
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deploy_api.py
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@ -52,6 +52,7 @@ async def idphoto_inference(
hd: bool = Form(True), hd: bool = Form(True),
dpi: int = Form(300), dpi: int = Form(300),
face_align: bool = Form(False), face_align: bool = Form(False),
whitening_strength: int = Form(0),
head_measure_ratio: float = Form(0.2), head_measure_ratio: float = Form(0.2),
head_height_ratio: float = Form(0.45), head_height_ratio: float = Form(0.45),
top_distance_max: float = Form(0.12), top_distance_max: float = Form(0.12),
@ -69,6 +70,8 @@ async def idphoto_inference(
image_bytes = await input_image.read() image_bytes = await input_image.read()
nparr = np.frombuffer(image_bytes, np.uint8) nparr = np.frombuffer(image_bytes, np.uint8)
img = cv2.imdecode(nparr, cv2.IMREAD_COLOR) img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
# 将BGR转换为RGB
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
# ------------------- 选择抠图与人脸检测模型 ------------------- # ------------------- 选择抠图与人脸检测模型 -------------------
choose_handler(creator, human_matting_model, face_detect_model) choose_handler(creator, human_matting_model, face_detect_model)
@ -83,6 +86,7 @@ async def idphoto_inference(
head_height_ratio=head_height_ratio, head_height_ratio=head_height_ratio,
head_top_range=(top_distance_max, top_distance_min), head_top_range=(top_distance_max, top_distance_min),
face_alignment=face_align, face_alignment=face_align,
whitening_strength=whitening_strength,
brightness_strength=brightness_strength, brightness_strength=brightness_strength,
contrast_strength=contrast_strength, contrast_strength=contrast_strength,
sharpen_strength=sharpen_strength, sharpen_strength=sharpen_strength,
@ -92,7 +96,7 @@ async def idphoto_inference(
result_message = {"status": False} result_message = {"status": False}
# 如果检测到人脸数量等于1, 则返回标准证和高清照结果（png 4通道图像） # 如果检测到人脸数量等于1, 则返回标准证和高清照结果（png 4通道图像）
else: else:
result_image_standard_bytes = save_image_dpi_to_bytes(cv2.cvtColor(result.standard, cv2.COLOR_RGBA2BGRA), None, dpi) result_image_standard_bytes = save_image_dpi_to_bytes(result.standard, None, dpi)
result_message = { result_message = {
"status": True, "status": True,
@ -101,7 +105,7 @@ async def idphoto_inference(
# 如果hd为True, 则增加高清照结果（png 4通道图像） # 如果hd为True, 则增加高清照结果（png 4通道图像）
if hd: if hd:
result_image_hd_bytes = save_image_dpi_to_bytes(cv2.cvtColor(result.hd, cv2.COLOR_RGBA2BGRA), None, dpi) result_image_hd_bytes = save_image_dpi_to_bytes(result.hd, None, dpi)
result_message["image_base64_hd"] = bytes_2_base64(result_image_hd_bytes) result_message["image_base64_hd"] = bytes_2_base64(result_image_hd_bytes)
return result_message return result_message