feat: move miniapp server project

sh/idcard/SegmentBody_01.sh

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+#!/bin/bash
+while true; do
+        if [ -f "stop.flag" ]; then
+                break
+        fi
+        curl http://47.111.93.124/index.php/api/sys/auto_deal_type_SegmentBody_01 -H 'Host:zhihuitb.zhonganonline.top' | sh
+        sleep 1;
+done

sh/idcard/idcard.py

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+import argparse
+import math
+import cv2
+
+from typing import List
+
+import numpy as np
+from alibabacloud_imageseg20191230.client import Client as imageseg20191230Client
+from alibabacloud_facebody20191230.client import Client as facebody20191230Client
+from alibabacloud_tea_openapi import models as open_api_models
+from alibabacloud_facebody20191230 import models as facebody_20191230_models
+from alibabacloud_imageseg20191230 import models as imageseg_20191230_models
+from alibabacloud_tea_util import models as util_models
+from alibabacloud_tea_util.client import Client as UtilClient
+from viapi.fileutils import FileUtils
+
+import urllib.request
+
+
+class Sample:
+    def __init__(self):
+        pass
+
+    @staticmethod
+    def create_client(
+            access_key_id: str,
+            access_key_secret: str,
+    ) -> (imageseg20191230Client, facebody20191230Client):
+        """
+        使用AK&SK初始化账号Client
+        @param access_key_id:
+        @param access_key_secret:
+        @return: Client
+        @throws Exception
+        """
+        seg_config = open_api_models.Config(
+            # 您的 AccessKey ID,
+            access_key_id=access_key_id,
+            # 您的 AccessKey Secret,
+            access_key_secret=access_key_secret
+        )
+        face_config = open_api_models.Config(
+            # 您的 AccessKey ID,
+            access_key_id=access_key_id,
+            # 您的 AccessKey Secret,
+            access_key_secret=access_key_secret
+        )
+        # 访问的域名
+        seg_config.endpoint = f'imageseg.cn-shanghai.aliyuncs.com'
+        face_config.endpoint = f'facebody.cn-shanghai.aliyuncs.com'
+        return (imageseg20191230Client(seg_config), facebody20191230Client(face_config))
+
+def id_pohto_demo(
+        args: List[str],
+) -> None:
+    assert (args is not None and len(args.param) > 2), "parameters wrong, use -h for details!"
+    [sc_file, color, of_file] = [i for i in args.param]
+
+    # set id photo size
+    size = [295, 413]
+
+    # client init
+    seg_client, face_client = Sample.create_client(args.access_key_id, args.access_key_secret)
+
+    # generation source image url
+    input_url = generate_url(sc_file, args.access_key_id, args.access_key_secret)
+
+    # init segment_body_request
+    segment_body_request = imageseg_20191230_models.SegmentBodyRequest(
+        image_url=input_url
+    )
+
+    # init detect_face_request
+    detect_face_request = facebody_20191230_models.DetectFaceRequest(
+        image_url=input_url
+    )
+    runtime = util_models.RuntimeOptions()
+    try:
+        # 通过人脸SDK获取人脸105关键点信息
+        face_result = face_client.detect_face_with_options(detect_face_request, runtime)
+        landmarks = face_result.body.data.landmarks
+        landmarks = np.array(landmarks)
+
+        # 通过分割SDK获取分割png图
+        seg_result = seg_client.segment_body_with_options(segment_body_request, runtime)
+        print(seg_result.body.data.image_url)
+        rqt = urllib.request.urlopen(seg_result.body.data.image_url)
+        seg_img = np.asarray(bytearray(rqt.read()), dtype="uint8")
+        seg_img = cv2.imdecode(seg_img, cv2.IMREAD_UNCHANGED)
+
+        # 根据人脸关键点进行人脸对齐，返回旋转后图像、面部中心点、旋转角度、旋转后新的landmarks值
+        rotated_img, eye_center, angle, landmarks = align_face(seg_img, landmarks)
+
+        # 输入旋转后图片、预期的证件照分辨率、landmarks、背景色，返回半身像结果
+        png_img = corp_halfbody(rotated_img, landmarks, size)
+
+        # 证件照背景色替换
+        colors = {'red': (0, 0, 255, 255), 'blue': (255, 0, 0, 255), 'white': (255, 255, 255, 255)}
+        if type(color) is str:
+            color = colors[color]
+        rst_img = np.zeros((size[1], size[0], 3)) + color[0:3]
+        rst_img = image_merge_background(png_img[:, :, 0:3], png_img, rst_img)
+
+        # 保存结果到本地
+        cv2.imwrite(of_file, rst_img)
+    except Exception as error:
+        print(error.message)
+        # 如有需要，请打印 error
+        UtilClient.assert_as_string(error.message)
+
+def align_face(image_array, landmarks):
+    """ align faces according to eyes position
+    :param image_array: numpy array of a single image
+    :param landmarks: dict of landmarks for facial parts as keys and tuple of coordinates as values
+    :return:
+    rotated_img:  numpy array of aligned image
+    eye_center: tuple of coordinates for eye center
+    angle: degrees of rotation
+    """
+    landmarks = np.resize(landmarks, (105, 2))
+
+    # get list landmarks of left and right eye
+    left_eye = landmarks[24:39]
+    right_eye = landmarks[40:55]
+    left_eye_center = np.mean(left_eye, axis=0).astype("int32")
+    right_eye_center = np.mean(right_eye, axis=0).astype("int32")
+    dy = right_eye_center[1] - left_eye_center[1]
+    dx = right_eye_center[0] - left_eye_center[0]
+    angle = math.atan2(dy, dx) * 180. / math.pi
+    # calculate the center of 2 eyes
+    eye_center = (int(left_eye_center[0] + right_eye_center[0]) // 2,
+                  int(left_eye_center[1] + right_eye_center[1]) // 2)
+    # at the eye_center, rotate the image by the angle
+    rotate_matrix = cv2.getRotationMatrix2D(eye_center, angle, scale=1)
+    rotated_img = cv2.warpAffine(image_array, rotate_matrix, (image_array.shape[1], image_array.shape[0]))
+
+    rotated_landmarks = []
+    for landmark in landmarks:
+        rotated_landmark = rotate(origin=eye_center, point=landmark, angle=angle, row=image_array.shape[0])
+        rotated_landmarks.append(rotated_landmark)
+    return rotated_img, eye_center, angle, rotated_landmarks
+
+def rotate(origin, point, angle, row):
+    """ rotate coordinates in image coordinate system
+    :param origin: tuple of coordinates,the rotation center
+    :param point: tuple of coordinates, points to rotate
+    :param angle: degrees of rotation
+    :param row: row size of the image
+    :return: rotated coordinates of point
+    """
+    x1, y1 = point
+    x2, y2 = origin
+    y1 = row - y1
+    y2 = row - y2
+    angle = math.radians(angle)
+    x = x2 + math.cos(angle) * (x1 - x2) - math.sin(angle) * (y1 - y2)
+    y = y2 + math.sin(angle) * (x1 - x2) + math.cos(angle) * (y1 - y2)
+    y = row - y
+    return int(x), int(y)
+
+def corp_halfbody(image_array, landmarks, size):
+    """ crop face according to eye,mouth and chin position
+    :param image_array: numpy array of a single image
+    :param size: single int value, size for w and h after crop
+    :param landmarks: dict of landmarks for facial parts as keys and tuple of coordinates as values
+    :return:
+    cropped_img: numpy array of cropped image
+    left, top: left and top coordinates of cropping
+    """
+
+    crop_size = [0, 0, size[1], size[0]]
+
+    scal = size[1] / 4 / abs(landmarks[98][1] - landmarks[56][1])
+    image = cv2.resize(image_array, np.multiply((image_array.shape[0:2])[::-1], scal).astype(int))
+    landmarks = np.multiply(np.array(landmarks), scal)
+
+    x_center = landmarks[98][0]
+    crop_size[0:2] = [x_center - size[0] / 2, x_center + size[0] / 2]
+
+    y_center = (landmarks[98][1] + landmarks[56][1]) / 2
+    crop_size[2:4] = [y_center - size[1] / 2, y_center + size[1] / 2]
+
+    left, right, top, bottom = [round(i) for i in crop_size]
+    left = max(0, left)
+    top = max(0, top)
+    right = min(image.shape[1], right)
+    bottom = min(image.shape[0], bottom)
+
+    cropped_img = image[top:bottom, left:right]
+
+    left, right, top, bottom = [round(i) for i in crop_size]
+    bottom = size[1]
+    top = size[1] - cropped_img.shape[0]
+    left = -min(0, left)
+    right = min(cropped_img.shape[1] + left, size[0])
+
+
+    png_img = np.zeros((size[1], size[0], 4))
+    png_img[top:bottom, left:right] = cropped_img[:, :]
+    return png_img
+
+def image_merge_background(sc_image, png_image, bg_image):
+    """ merge foreground to background image
+    :param sc_image: numpy array of the source image
+    :param png_image: numpy array of the segmented result with same size of sc_image
+    :param bg_image: numpy array of the background image with same size of sc_image
+    :return:
+    rst_image: numpy array of merged image
+    """
+    assert (sc_image is not None and png_image is not None and bg_image is not None), "read image input error!"
+    h, w, c = sc_image.shape
+
+    # keep sc_image, png_image and bg_image same size
+    viapi_image = cv2.resize(png_image, (w, h))
+    bg_image = cv2.resize(bg_image, (w, h))
+    if len(viapi_image.shape) == 2:
+        mask = viapi_image[:, :, np.newaxis]
+    elif viapi_image.shape[2] == 4:
+        mask = viapi_image[:, :, 3:4]
+    elif viapi_image.shape[2] == 3:
+        mask = viapi_image[:, :, 0:1]
+    else:
+        raise Exception("invalid image mask!")
+    mask = mask / 255.0
+
+    # merge background
+    sc_image = sc_image.astype(float)
+    bg_image = bg_image.astype(float)
+    rst_image = (sc_image - bg_image) * mask + bg_image
+    rst_image = np.clip(rst_image, 0, 255)
+    return rst_image
+
+# see https://help.aliyun.com/document_detail/155645.html for more detail
+def generate_url(image_path, access_key_id, access_key_secret):
+    file_utils = FileUtils(access_key_id, access_key_secret)
+    oss_url = file_utils.get_oss_url(image_path, "jpeg", True)
+    return oss_url
+
+def define_options():
+    parser = argparse.ArgumentParser(description='Human segmentation examples.')
+    parser.add_argument('-i', '--access_key_id', default="LTAI5tE6gkXQqJBbCxFfo4hv", help="oss access key id")
+    parser.add_argument('-s', '--access_key_secret', default="pziJRQfXlev3vEIY4dHuB6C7E73Uv6", help="access key secret")
+    parser.add_argument('-p', '--param', nargs=3
+                            , default=['./data/source.jpeg', 'blue', 'result2.jpg']
+                            , type=str
+                            , help=('source_image_path background_color[red blue white] result_path'))
+    args = parser.parse_args()
+    return args
+
+if __name__ == '__main__':
+    args = define_options()
+    id_pohto_demo(args)