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from fastapi import FastAPI, UploadFile, Form
import onnxruntime
from src.face_judgement_align import IDphotos_create
from src.layoutCreate import generate_layout_photo, generate_layout_image
from hivisionai.hycv.vision import add_background
import base64
import numpy as np
import cv2
import ast
app = FastAPI()
# 将图像转换为Base64编码
def numpy_2_base64(img: np.ndarray):
retval, buffer = cv2.imencode('.png', img)
base64_image = base64.b64encode(buffer).decode('utf-8')
return base64_image
# 证件照智能制作接口
@app.post("/idphoto")
async def idphoto_inference(input_image: UploadFile,
size: str = Form(...),
head_measure_ratio=0.2,
head_height_ratio=0.45,
top_distance_max=0.12,
top_distance_min=0.10):
image_bytes = await input_image.read()
nparr = np.frombuffer(image_bytes, np.uint8)
img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
# 将字符串转为元组
size = ast.literal_eval(size)
result_image_hd, result_image_standard, typography_arr, typography_rotate, \
_, _, _, _, status = IDphotos_create(img,
size=size,
head_measure_ratio=head_measure_ratio,
head_height_ratio=head_height_ratio,
align=False,
beauty=False,
fd68=None,
human_sess=sess,
IS_DEBUG=False,
top_distance_max=top_distance_max,
top_distance_min=top_distance_min)
# 如果检测到人脸数量不等于1（照片无人脸 or 多人脸）
if status == 0:
result_messgae = {
"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）
else:
result_messgae = {
"status": True,
"img_output_standard": numpy_2_base64(result_image_standard),
"img_output_standard_hd": numpy_2_base64(result_image_hd),
}
return result_messgae
# 透明图像添加纯色背景接口
@app.post("/add_background")
async def photo_add_background(input_image: UploadFile,
color: str = Form(...)):
# 读取图像
image_bytes = await input_image.read()
nparr = np.frombuffer(image_bytes, np.uint8)
img = cv2.imdecode(nparr, cv2.IMREAD_UNCHANGED)
# 将字符串转为元组
color = ast.literal_eval(color)
# 将元祖的0和2号数字交换
color = (color[2], color[1], color[0])
# try:
result_messgae = {
"status": True,
"image": numpy_2_base64(add_background(img, bgr=color)),
}
# except Exception as e:
# print(e)
# result_messgae = {
# "status": False,
# "error": e
# }
return result_messgae
# 六寸排版照生成接口
@app.post("/generate_layout_photos")
async def generate_layout_photos(input_image: UploadFile, size: str = Form(...)):
try:
image_bytes = await input_image.read()
nparr = np.frombuffer(image_bytes, np.uint8)
img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
size = ast.literal_eval(size)
typography_arr, typography_rotate = generate_layout_photo(input_height=size[0],
input_width=size[1])
result_layout_image = generate_layout_image(img, typography_arr,
typography_rotate,
height=size[0],
width=size[1])
result_messgae = {
"status": True,
"image": numpy_2_base64(result_layout_image),
}
except Exception as e:
result_messgae = {
"status": False,
}
return result_messgae
if __name__ == "__main__":
import uvicorn
# 加载权重文件
HY_HUMAN_MATTING_WEIGHTS_PATH = "./hivision_modnet.onnx"
sess = onnxruntime.InferenceSession(HY_HUMAN_MATTING_WEIGHTS_PATH)
# 在8080端口运行推理服务
uvicorn.run(app, host="0.0.0.0", port=8080)
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