#!/usr/bin/env python # -*- coding: UTF-8 -*- """ @Project ：trinity_client @File ：synthesis_item.py @Author ：周成融 @Date ：2023/8/26 14:13:04 @detail ： """ import io import logging import time # import boto3 import cv2 import numpy as np from PIL import Image from minio import Minio from app.core.config import * from app.service.utils.decorator import RunTime from app.service.utils.generate_uuid import generate_uuid minio_client = Minio( MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE) # s3 = boto3.client( # 's3', # aws_access_key_id=S3_ACCESS_KEY, # aws_secret_access_key=S3_AWS_SECRET_ACCESS_KEY, # region_name=S3_REGION_NAME # ) def positioning(all_mask_shape, mask_shape, offset): all_start = 0 all_end = 0 mask_start = 0 mask_end = 0 if offset == 0: all_start = 0 all_end = min(all_mask_shape, mask_shape) mask_start = 0 mask_end = min(all_mask_shape, mask_shape) elif offset > 0: all_start = min(offset, all_mask_shape) all_end = min(offset + mask_shape, all_mask_shape) mask_start = 0 mask_end = 0 if offset > all_mask_shape else min(all_mask_shape - offset, mask_shape) elif offset < 0: if abs(offset) > mask_shape: all_start = 0 all_end = 0 else: all_start = 0 if mask_shape - abs(offset) > all_mask_shape: all_end = min(mask_shape - abs(offset), all_mask_shape) else: all_end = mask_shape - abs(offset) if abs(offset) > mask_shape: mask_start = mask_shape mask_end = mask_shape else: mask_start = abs(offset) if mask_shape - abs(offset) >= all_mask_shape: mask_end = all_mask_shape + abs(offset) else: mask_end = mask_shape return all_start, all_end, mask_start, mask_end # @RunTime def synthesis(data, size): # 创建底图 base_image = Image.new('RGBA', size, (0, 0, 0, 0)) try: all_mask_shape = (size[1], size[0]) top_outer_mask = np.zeros(all_mask_shape, dtype=np.uint8) bottom_outer_mask = np.zeros(all_mask_shape, dtype=np.uint8) top = True bottom = True i = len(data) while i: i -= 1 if top and data[i]['name'] in ["blouse_front", "outwear_front", "dress_front", "tops_front"]: top = False mask_shape = data[i]['mask'].shape y_offset, x_offset = data[i]['position'] # 初始化叠加区域的起始和结束位置 all_y_start, all_y_end, mask_y_start, mask_y_end = positioning(all_mask_shape=all_mask_shape[0], mask_shape=mask_shape[0], offset=y_offset) all_x_start, all_x_end, mask_x_start, mask_x_end = positioning(all_mask_shape=all_mask_shape[1], mask_shape=mask_shape[1], offset=x_offset) # 将叠加区域赋值为相应的像素值 top_outer_mask[all_y_start:all_y_end, all_x_start:all_x_end] = data[i]['mask'][mask_y_start:mask_y_end, mask_x_start:mask_x_end] elif bottom and data[i]['name'] in ["trousers_front", "skirt_front", "bottoms_front"]: bottom = False mask_shape = data[i]['mask'].shape y_offset, x_offset = data[i]['position'] # 初始化叠加区域的起始和结束位置 all_y_start, all_y_end, mask_y_start, mask_y_end = positioning(all_mask_shape=all_mask_shape[0], mask_shape=mask_shape[0], offset=y_offset) all_x_start, all_x_end, mask_x_start, mask_x_end = positioning(all_mask_shape=all_mask_shape[1], mask_shape=mask_shape[1], offset=x_offset) # 将叠加区域赋值为相应的像素值 bottom_outer_mask[all_y_start:all_y_end, all_x_start:all_x_end] = data[i]['mask'][mask_y_start:mask_y_end, mask_x_start:mask_x_end] elif bottom is False and top is False: break all_mask = cv2.bitwise_or(top_outer_mask, bottom_outer_mask) for layer in data: if layer['image'] is not None: if layer['name'] != "body": test_image = Image.new('RGBA', size, (0, 0, 0, 0)) test_image.paste(layer['image'], (layer['position'][1], layer['position'][0]), layer['image']) mask_data = np.where(all_mask > 0, 255, 0).astype(np.uint8) mask_alpha = Image.fromarray(mask_data) cropped_image = Image.composite(test_image, Image.new("RGBA", test_image.size, (255, 255, 255, 0)), mask_alpha) base_image.paste(cropped_image, (0, 0), cropped_image) else: base_image.paste(layer['image'], (layer['position'][1], layer['position'][0]), layer['image']) result_image = base_image with io.BytesIO() as output: result_image.save(output, format='PNG') data = output.getvalue() image_data = io.BytesIO() result_image.save(image_data, format='PNG') image_data.seek(0) image_bytes = image_data.read() return f"aida-results/{minio_client.put_object('aida-results', f'result_{generate_uuid()}.png', io.BytesIO(image_bytes), len(image_bytes), content_type='image/png').object_name}" # object_name = f'result_{generate_uuid()}.png' # response = s3.put_object(Bucket="aida-results", Key=object_name, Body=data, ContentType='image/png') # object_url = f"aida-results/{object_name}" # if response['ResponseMetadata']['HTTPStatusCode'] == 200: # return object_url # else: # return "" except Exception as e: logging.warning(f"synthesis runtime exception : {e}") def synthesis_single(front_image, back_image): result_image = None if front_image: result_image = front_image if back_image: result_image.paste(back_image, (0, 0), back_image) # with io.BytesIO() as output: # result_image.save(output, format='PNG') # data = output.getvalue() # object_name = f'result_{generate_uuid()}.png' # response = s3.put_object(Bucket="aida-results", Key=object_name, Body=data, ContentType='image/png') # object_url = f"aida-results/{object_name}" # if response['ResponseMetadata']['HTTPStatusCode'] == 200: # return object_url # else: # return "" image_data = io.BytesIO() result_image.save(image_data, format='PNG') image_data.seek(0) image_bytes = image_data.read() return f"aida-results/{minio_client.put_object('aida-results', f'result_{generate_uuid()}.png', io.BytesIO(image_bytes), len(image_bytes), content_type='image/png').object_name}"