diff --git a/app/api/api_mannequins_edit.py b/app/api/api_mannequins_edit.py index 5cfaf3d..9eec805 100644 --- a/app/api/api_mannequins_edit.py +++ b/app/api/api_mannequins_edit.py @@ -24,9 +24,11 @@ def mannequins_edit(request_data: MannequinModel): 示例参数： - **{ "mannequins": "aida-sys-image/models/male/dc36ce58-46c3-4b6f-8787-5ca7d6fc26e6.png", - "scale": [0.75, 0.75], + "scale": 0.75, "bucket_name": "test", - "mannequin_name": "mannequin_name" + "mannequin_name": "mannequin_name", + "top" : 270, + "bottom" : 432 }** """ try: diff --git a/app/schemas/mannequin_edit.py b/app/schemas/mannequin_edit.py index c5514d6..2a8f5f9 100644 --- a/app/schemas/mannequin_edit.py +++ b/app/schemas/mannequin_edit.py @@ -3,6 +3,8 @@ from pydantic import BaseModel class MannequinModel(BaseModel): mannequins: str - scale: list[float, float] + scale: float bucket_name: str mannequin_name: str + top: int + bottom: int diff --git a/app/service/mannequins_edit/service.py b/app/service/mannequins_edit/service.py index bbb6cc5..685709f 100644 --- a/app/service/mannequins_edit/service.py +++ b/app/service/mannequins_edit/service.py @@ -1,5 +1,4 @@ import cv2 -import mediapipe as mp import numpy as np from minio import Minio @@ -13,6 +12,8 @@ minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET class MannequinEditService(): def __init__(self, request_data): self.scale = request_data.scale + self.top = request_data.top + self.bottom = request_data.bottom self.image = oss_get_image(oss_client=minio_client, bucket=request_data.mannequins.split('/')[0], object_name=request_data.mannequins[request_data.mannequins.find('/') + 1:], data_type="cv2") self.mannequin_name = request_data.mannequin_name self.bucket_name = request_data.bucket_name @@ -27,59 +28,33 @@ class MannequinEditService(): self.alpha = None def __call__(self, *args, **kwargs): - leg_top, leg_bottom = self.attitude_detection() - if leg_top and leg_bottom: - new_mannequin = self.resize_leg(leg_top, leg_bottom) - _, encoded_image = cv2.imencode('.png', new_mannequin) - image_bytes = encoded_image.tobytes() - req = oss_upload_image(oss_client=minio_client, bucket=self.bucket_name, object_name=f"{self.mannequin_name}.png", image_bytes=image_bytes) - return req.bucket_name + "/" + req.object_name - else: - return "No leg detected" + new_mannequin = self.resize_leg(self.top, self.bottom) + _, encoded_image = cv2.imencode('.png', new_mannequin) + image_bytes = encoded_image.tobytes() + req = oss_upload_image(oss_client=minio_client, bucket=self.bucket_name, object_name=f"{self.mannequin_name}.png", image_bytes=image_bytes) + return req.bucket_name + "/" + req.object_name - def attitude_detection(self): - mp_pose = mp.solutions.pose - pose = mp_pose.Pose() + def resize_leg(self, top, bottom): + # 上部 + top_part = self.bgr[:top, :] + top_part_alpha = self.alpha[:top, :] - # 将 BGR 图像转换为 RGB 格式 - image_rgb = cv2.cvtColor(self.bgr, cv2.COLOR_BGR2RGB) - leg_top, leg_bottom = None, None - # 进行姿态检测 - results = pose.process(image_rgb) - if results.pose_landmarks: - # 获取腿部关键点 - landmarks = results.pose_landmarks.landmark + # 需要resize 部分 + part_resize = self.bgr[top:bottom, :] + part_resize_alpha = self.alpha[top:bottom, :] - # 找到腿部上边界和下边界 - leg_top = int(landmarks[mp_pose.PoseLandmark.LEFT_HIP].y * self.h) - leg_bottom = int(max(landmarks[mp_pose.PoseLandmark.LEFT_ANKLE].y, - landmarks[mp_pose.PoseLandmark.RIGHT_ANKLE].y) * self.h) + # 下部 + part_bottom = self.bgr[bottom:, :] + part_bottom_alpha = self.alpha[bottom:, :] - return leg_top, leg_bottom + new_height = int((bottom - top) * self.scale) - def resize_leg(self, leg_top, leg_bottom): - # 上半身 - top_part_bgr = self.bgr[:leg_top, :] - top_part_bgr_alpha = self.alpha[:leg_top, :] + resized_thigh = cv2.resize(part_resize, (self.w, new_height), interpolation=cv2.INTER_LINEAR) + resized_thigh_alpha = cv2.resize(part_resize_alpha, (self.w, new_height), interpolation=cv2.INTER_LINEAR) - # 小腿 - part_thigh = self.bgr[leg_top:leg_bottom, :] - part_thigh_alpha = self.alpha[leg_top:leg_bottom, :] - - # 大腿 - part_calf = self.bgr[leg_bottom:, :] - part_calf_alpha = self.alpha[leg_bottom:, :] - - new_thigh_height = int((leg_bottom - leg_top) * self.scale[0]) - new_calf_height = int((self.h - leg_bottom) * self.scale[1]) - - resized_thigh = cv2.resize(part_thigh, (self.w, new_thigh_height), interpolation=cv2.INTER_LINEAR) - resized_thigh_alpha = cv2.resize(part_thigh_alpha, (self.w, new_thigh_height), interpolation=cv2.INTER_LINEAR) - resized_calf = cv2.resize(part_calf, (self.w, new_calf_height), interpolation=cv2.INTER_LINEAR) - resized_calf_alpha = cv2.resize(part_calf_alpha, (self.w, new_calf_height), interpolation=cv2.INTER_LINEAR) - - new_bgr = np.vstack((top_part_bgr, resized_thigh, resized_calf)) - new_bgr_alpha = np.vstack((top_part_bgr_alpha, resized_thigh_alpha, resized_calf_alpha)) + # 组合 + new_bgr = np.vstack((top_part, resized_thigh, part_bottom)) + new_bgr_alpha = np.vstack((top_part_alpha, resized_thigh_alpha, part_bottom_alpha)) if self.alpha is not None: # 拼接 alpha 通道 @@ -93,9 +68,11 @@ class MannequinEditService(): if __name__ == '__main__': request_data = MannequinModel( mannequins="aida-sys-image/models/male/dc36ce58-46c3-4b6f-8787-5ca7d6fc26e6.png", - scale=[0.75, 0.75], + scale=0.1, bucket_name="test", - mannequin_name="mannequin_name" + mannequin_name="mannequin_name", + top=270, + bottom=432 ) service = MannequinEditService(request_data) print(service())