From 2df1518a9957cda75b3df1bad3c30362dc50a9b7 Mon Sep 17 00:00:00 2001 From: zhouchengrong Date: Fri, 21 Jun 2024 17:13:39 +0800 Subject: [PATCH] feat fix minio and s3 --- app/api/api_test.py | 3 +- .../attribute/service_att_recognition.py | 11 +- .../attribute/service_category_recognition.py | 10 +- .../design/items/pipelines/keypoints.py | 8 +- app/service/design/items/pipelines/loading.py | 60 +++++---- .../design/items/pipelines/painting.py | 77 +++++++----- app/service/design/items/pipelines/split.py | 2 +- app/service/design_pre_processing/service.py | 117 ++++++++++++------ .../generate_image/service_generate_image.py | 13 +- app/service/super_resolution/service.py | 33 +++-- app/service/utils/oss_client.py | 12 +- 11 files changed, 200 insertions(+), 146 deletions(-) diff --git a/app/api/api_test.py b/app/api/api_test.py index 86ed25c..0ff521a 100644 --- a/app/api/api_test.py +++ b/app/api/api_test.py @@ -1,6 +1,6 @@ import logging from fastapi import APIRouter -from app.core.config import SR_RABBITMQ_QUEUES, GI_RABBITMQ_QUEUES, GPI_RABBITMQ_QUEUES, GRI_RABBITMQ_QUEUES +from app.core.config import SR_RABBITMQ_QUEUES, GI_RABBITMQ_QUEUES, GPI_RABBITMQ_QUEUES, GRI_RABBITMQ_QUEUES, OSS from fastapi import FastAPI, HTTPException from app.schemas.response_template import ResponseModel @@ -16,6 +16,7 @@ def test(id: int): "GI_RABBITMQ_QUEUES": GI_RABBITMQ_QUEUES, "GPI_RABBITMQ_QUEUES": GPI_RABBITMQ_QUEUES, "GRI_RABBITMQ_QUEUES": GRI_RABBITMQ_QUEUES, + "local_oss_server": OSS } logger.info(data) if id == 1: diff --git a/app/service/attribute/service_att_recognition.py b/app/service/attribute/service_att_recognition.py index da71c16..ddcfd1c 100644 --- a/app/service/attribute/service_att_recognition.py +++ b/app/service/attribute/service_att_recognition.py @@ -11,12 +11,12 @@ from minio import Minio import tritonclient.http as httpclient from app.core.config import * from app.schemas.attribute_retrieve import AttributeRecognitionModel +from app.service.utils.oss_client import oss_get_image class AttributeRecognition: def __init__(self, const, request_data): - self.minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE) - logging.info("实例化完成") + # self.minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE) self.request_data = [] for i, sketch in enumerate(request_data): self.request_data.append( @@ -97,9 +97,10 @@ class AttributeRecognition: return res def get_image(self, url): - response = self.minio_client.get_object(url.split("/", 1)[0], url.split("/", 1)[1]) - img = np.frombuffer(response.data, np.uint8) # 转成8位无符号整型 - img = cv2.imdecode(img, cv2.IMREAD_COLOR) # 解码 + # response = self.minio_client.get_object(url.split("/", 1)[0], url.split("/", 1)[1]) + # img = np.frombuffer(response.data, np.uint8) # 转成8位无符号整型 + # img = cv2.imdecode(img, cv2.IMREAD_COLOR) # + img = oss_get_image(bucket=url.split("/", 1)[0], object_name=url.split("/", 1)[1], data_type="cv2") img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) return img diff --git a/app/service/attribute/service_category_recognition.py b/app/service/attribute/service_category_recognition.py index 18ee043..fb997e9 100644 --- a/app/service/attribute/service_category_recognition.py +++ b/app/service/attribute/service_category_recognition.py @@ -18,12 +18,13 @@ import torch from app.core.config import * from app.schemas.attribute_retrieve import CategoryRecognitionModel +from app.service.utils.oss_client import oss_get_image class CategoryRecognition: def __init__(self, request_data): self.attr_type = pd.read_csv(CATEGORY_PATH) - self.minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE) + # self.minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE) self.request_data = [] self.triton_client = httpclient.InferenceServerClient(url=ATT_TRITON_URL) for sketch in request_data: @@ -51,9 +52,10 @@ class CategoryRecognition: def get_image(self, url): # Get data of an object. # Read data from response. - response = self.minio_client.get_object(url.split("/", 1)[0], url.split("/", 1)[1]) - img = np.frombuffer(response.data, np.uint8) # 转成8位无符号整型 - img = cv2.imdecode(img, cv2.IMREAD_COLOR) # 解码 + # response = self.minio_client.get_object(url.split("/", 1)[0], url.split("/", 1)[1]) + # img = np.frombuffer(response.data, np.uint8) # 转成8位无符号整型 + # img = cv2.imdecode(img, cv2.IMREAD_COLOR) # 解码 + img = oss_get_image(bucket=url.split("/", 1)[0], object_name=url.split("/", 1)[1], data_type="cv2") img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB) return img diff --git a/app/service/design/items/pipelines/keypoints.py b/app/service/design/items/pipelines/keypoints.py index 6cf1141..1f53ced 100644 --- a/app/service/design/items/pipelines/keypoints.py +++ b/app/service/design/items/pipelines/keypoints.py @@ -1,5 +1,6 @@ import logging import time + import numpy as np from pymilvus import MilvusClient @@ -71,11 +72,8 @@ class KeypointDetection(object): ] try: client = MilvusClient(uri=MILVUS_URL, token=MILVUS_TOKEN, db_name=MILVUS_ALIAS) - start_time = time.time() - res = client.upsert( - collection_name=MILVUS_TABLE_KEYPOINT, - data=data, - ) + # start_time = time.time() + res = client.upsert(collection_name=MILVUS_TABLE_KEYPOINT, data=data) # logging.info(f"save keypoint time : {time.time() - start_time}") client.close() return dict(zip(KEYPOINT_RESULT_TABLE_FIELD_SET, result.reshape(12, 2).astype(int).tolist())) diff --git a/app/service/design/items/pipelines/loading.py b/app/service/design/items/pipelines/loading.py index 2697006..a1a49a5 100644 --- a/app/service/design/items/pipelines/loading.py +++ b/app/service/design/items/pipelines/loading.py @@ -1,6 +1,5 @@ import io import logging -import time import cv2 import numpy as np @@ -8,6 +7,7 @@ from PIL import Image from minio import Minio from app.core.config import * +from app.service.utils.oss_client import oss_get_image from ..builder import PIPELINES @@ -70,11 +70,7 @@ class LoadImageFromFile(object): class LoadBodyImageFromFile(object): def __init__(self, body_path): self.body_path = body_path - self.minioClient = Minio( - f"{MINIO_URL}", - access_key=MINIO_ACCESS, - secret_key=MINIO_SECRET, - secure=MINIO_SECURE) + # self.minioClient = Minio(f"{MINIO_URL}", access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE) # response = self.minioClient.get_object("aida-mannequins", "model_1693218345.2714431.png") @@ -82,33 +78,33 @@ class LoadBodyImageFromFile(object): def __call__(self, result): result["image_url"] = result['body_path'] = self.body_path result["name"] = "mannequin" - if not result['image_url'].lower().endswith(".png"): - logging.info(1) - bucket = self.body_path.split("/", 1)[0] - object_name = self.body_path.split("/", 1)[1] - new_object_name = f'{object_name[:object_name.rfind(".")]}.png' - image = self.minioClient.get_object(bucket, object_name) - image = Image.open(io.BytesIO(image.data)) - image = image.convert("RGBA") - data = image.getdata() - # - new_data = [] - for item in data: - if item[0] >= 230 and item[1] >= 230 and item[2] >= 230: - new_data.append((255, 255, 255, 0)) - else: - new_data.append(item) - image.putdata(new_data) - image_data = io.BytesIO() - image.save(image_data, format='PNG') - image_data.seek(0) - image_bytes = image_data.read() - image_path = f"{bucket}/{self.minioClient.put_object(bucket, new_object_name, io.BytesIO(image_bytes), len(image_bytes), content_type='image/png').object_name}" - self.body_path = image_path - result["image_url"] = result['body_path'] = self.body_path - response = self.minioClient.get_object(self.body_path.split("/", 1)[0], self.body_path.split("/", 1)[1]) + # if not result['image_url'].lower().endswith(".png"): + # bucket = self.body_path.split("/", 1)[0] + # object_name = self.body_path.split("/", 1)[1] + # new_object_name = f'{object_name[:object_name.rfind(".")]}.png' + # image = self.minioClient.get_object(bucket, object_name) + # image = Image.open(io.BytesIO(image.data)) + # image = image.convert("RGBA") + # data = image.getdata() + # # + # new_data = [] + # for item in data: + # if item[0] >= 230 and item[1] >= 230 and item[2] >= 230: + # new_data.append((255, 255, 255, 0)) + # else: + # new_data.append(item) + # image.putdata(new_data) + # image_data = io.BytesIO() + # image.save(image_data, format='PNG') + # image_data.seek(0) + # image_bytes = image_data.read() + # image_path = f"{bucket}/{self.minioClient.put_object(bucket, new_object_name, io.BytesIO(image_bytes), len(image_bytes), content_type='image/png').object_name}" + # self.body_path = image_path + # result["image_url"] = result['body_path'] = self.body_path + # response = self.minioClient.get_object(self.body_path.split("/", 1)[0], self.body_path.split("/", 1)[1]) # put_image_time = time.time() - result['body_image'] = Image.open(io.BytesIO(response.read())) + # result['body_image'] = Image.open(io.BytesIO(response.read())) + result['body_image'] = oss_get_image(bucket=self.body_path.split("/", 1)[0], object_name=self.body_path.split("/", 1)[1], data_type="PIL") # logging.info(f"Image.open time is : {time.time() - put_image_time}") return result diff --git a/app/service/design/items/pipelines/painting.py b/app/service/design/items/pipelines/painting.py index 6d88411..3c9c233 100644 --- a/app/service/design/items/pipelines/painting.py +++ b/app/service/design/items/pipelines/painting.py @@ -1,19 +1,16 @@ import random -from io import BytesIO + # 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.oss_client import oss_get_image from ..builder import PIPELINES -minio_client = Minio( - MINIO_URL, - access_key=MINIO_ACCESS, - secret_key=MINIO_SECRET, - secure=MINIO_SECURE) + +# 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) @@ -56,17 +53,18 @@ class Painting(object): @staticmethod def get_gradient(bucket_name, object_name): - image_data = minio_client.get_object(bucket_name, object_name) + # image_data = minio_client.get_object(bucket_name, object_name) # image_data = s3.get_object(Bucket=bucket_name, Key=object_name)['Body'] # 从数据流中读取图像 - image_bytes = image_data.read() + # image_bytes = image_data.read() # 将图像数据转换为numpy数组 - image_array = np.asarray(bytearray(image_bytes), dtype=np.uint8) + # image_array = np.asarray(bytearray(image_bytes), dtype=np.uint8) # 使用OpenCV解码图像数组 - image = cv2.imdecode(image_array, cv2.IMREAD_COLOR) + # image = cv2.imdecode(image_array, cv2.IMREAD_COLOR) + image = oss_get_image(bucket=bucket_name, object_name=object_name, data_type="cv2") return image @staticmethod @@ -494,16 +492,20 @@ class PrintPainting(object): if not 'IfSingle' in print_dict.keys(): print_dict['IfSingle'] = False - data = minio_client.get_object(print_dict['print_path_list'][0].split("/", 1)[0], print_dict['print_path_list'][0].split("/", 1)[1]) - # data = s3.get_object(Bucket=print_dict['print_path_list'][0].split("/", 1)[0], Key=print_dict['print_path_list'][0].split("/", 1)[1])['Body'] + # data = minio_client.get_object(print_dict['print_path_list'][0].split("/", 1)[0], print_dict['print_path_list'][0].split("/", 1)[1]) + # data_bytes = BytesIO(data.read()) + # image = Image.open(data_bytes) + # image_mode = image.mode - data_bytes = BytesIO(data.read()) - image = Image.open(data_bytes) - image_mode = image.mode + bucket_name = print_dict['print_path_list'][0].split("/", 1)[0] + object_name = print_dict['print_path_list'][0].split("/", 1)[1] + image = oss_get_image(bucket=bucket_name, object_name=object_name, data_type="cv2") # 判断图片格式，如果是RGBA 则贴在一张纯白图片上 防止透明转黑 - if image_mode == "RGBA": - new_background = Image.new('RGB', image.size, (255, 255, 255)) - new_background.paste(image, mask=image.split()[3]) + if image.shape[2] == 4: + image_rgb = cv2.cvtColor(image, cv2.COLOR_BGRA2RGBA) + image_pil = Image.fromarray(image_rgb) + new_background = Image.new('RGB', image_pil.size, (255, 255, 255)) + new_background.paste(image_pil, mask=image.split()[3]) image = new_background print_dict['image'] = cv2.cvtColor(np.asarray(image), cv2.COLOR_RGB2BGR) @@ -577,21 +579,30 @@ class PrintPainting(object): @staticmethod def read_image(image_url): - data = minio_client.get_object(image_url.split("/", 1)[0], image_url.split("/", 1)[1]) - # data = s3.get_object(Bucket=image_url.split("/", 1)[0], Key=image_url.split("/", 1)[1])['Body'] - - data_bytes = BytesIO(data.read()) - image = Image.open(data_bytes) - image_mode = image.mode - # 判断图片格式，如果是RGBA 则贴在一张纯白图片上 防止透明转黑 - if image_mode == "RGBA": - # new_background = Image.new('RGB', image.size, (255, 255, 255)) - # new_background.paste(image, mask=image.split()[3]) - # image = new_background - return image, image_mode - image = cv2.cvtColor(np.asarray(image), cv2.COLOR_RGB2BGR) + image = oss_get_image(bucket=image_url.split("/", 1)[0], object_name=image_url.split("/", 1)[1], data_type="cv2") + if image.shape[2] == 4: + image_rgb = cv2.cvtColor(image, cv2.COLOR_BGRA2RGBA) + image = Image.fromarray(image_rgb) + image_mode = "RGBA" + else: + image_mode = "RGB" return image, image_mode + # data = minio_client.get_object(image_url.split("/", 1)[0], image_url.split("/", 1)[1]) + # # data = s3.get_object(Bucket=image_url.split("/", 1)[0], Key=image_url.split("/", 1)[1])['Body'] + # + # data_bytes = BytesIO(data.read()) + # image = Image.open(data_bytes) + # image_mode = image.mode + # # 判断图片格式，如果是RGBA 则贴在一张纯白图片上 防止透明转黑 + # if image_mode == "RGBA": + # # new_background = Image.new('RGB', image.size, (255, 255, 255)) + # # new_background.paste(image, mask=image.split()[3]) + # # image = new_background + # return image, image_mode + # image = cv2.cvtColor(np.asarray(image), cv2.COLOR_RGB2BGR) + # return image, "RGB" + # @staticmethod # def read_image(image_url): # response = requests.get(image_url) diff --git a/app/service/design/items/pipelines/split.py b/app/service/design/items/pipelines/split.py index e46a3e1..0183352 100644 --- a/app/service/design/items/pipelines/split.py +++ b/app/service/design/items/pipelines/split.py @@ -41,7 +41,7 @@ class Split(object): else: back_mask = result['back_mask'] - rgba_image = rgb_to_rgba((result['final_image'].shape[0], result['final_image'].shape[1]), result['final_image'], result['mask']) + rgba_image = rgb_to_rgba((result['final_image'].shape[0], result['final_image'].shape[1]), re4sult['final_image'], result['mask']) result_front_image = np.zeros_like(rgba_image) result_front_image[front_mask != 0] = rgba_image[front_mask != 0] diff --git a/app/service/design_pre_processing/service.py b/app/service/design_pre_processing/service.py index e655087..88ed739 100644 --- a/app/service/design_pre_processing/service.py +++ b/app/service/design_pre_processing/service.py @@ -13,15 +13,12 @@ import io from app.core.config import * from app.service.design.utils.design_ensemble import get_keypoint_result +from app.service.utils.oss_client import oss_get_image, oss_upload_image class DesignPreprocessing: - def __init__(self): - self.minio_client = Minio( - MINIO_URL, - access_key=MINIO_ACCESS, - secret_key=MINIO_SECRET, - secure=MINIO_SECURE) + # def __init__(self): + # self.minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE) # @ RunTime def pipeline(self, image_list): @@ -51,8 +48,9 @@ class DesignPreprocessing: def read_image(self, image_list): for obj in image_list: - file = self.minio_client.get_object(obj['image_url'].split("/", 1)[0], obj['image_url'].split("/", 1)[1]).data - image = cv2.imdecode(np.frombuffer(file, np.uint8), 1) + # file = self.minio_client.get_object(obj['image_url'].split("/", 1)[0], obj['image_url'].split("/", 1)[1]).data + # image = cv2.imdecode(np.frombuffer(file, np.uint8), 1) + image = oss_get_image(bucket=obj['image_url'].split("/", 1)[0], object_name=obj['image_url'].split("/", 1)[1], data_type="cv2") if len(image.shape) == 2: image = cv2.cvtColor(image, cv2.COLOR_GRAY2RGB) elif image.shape[2] == 4: # 如果是四通道 mask @@ -125,7 +123,10 @@ class DesignPreprocessing: try: # 覆盖到minio image_bytes = cv2.imencode(".jpg", item['obj'])[1].tobytes() - self.minio_client.put_object(item['image_url'].split("/", 1)[0], item['image_url'].split("/", 1)[1], io.BytesIO(image_bytes), len(image_bytes), content_type="image/jpeg", ) + # self.minio_client.put_object(item['image_url'].split("/", 1)[0], item['image_url'].split("/", 1)[1], io.BytesIO(image_bytes), len(image_bytes), content_type="image/jpeg", ) + bucket_name = item['image_url'].split("/", 1)[0] + object_name = item['image_url'].split("/", 1)[1] + oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=image_bytes) print(f"Object '{item['image_url'].split('/', 1)[1]}' overwritten successfully.") except ResponseError as err: print(f"Error: {err}") @@ -165,36 +166,76 @@ class DesignPreprocessing: # @ RunTime def composing_image(self, image_list): for image in image_list: - if image['site'] == 'down': - image_width = image['obj'].shape[1] - waist_width = image['keypoint_result']['waistband_right'][1] - image['keypoint_result']['waistband_left'][1] - scale = 0.4 - if waist_width / scale >= image['obj'].shape[1]: - add_width = int((waist_width / scale - image_width) / 2) - ret = cv2.copyMakeBorder(image['obj'], 0, 0, add_width, add_width, cv2.BORDER_CONSTANT, value=(256, 256, 256)) - if IF_DEBUG_SHOW: - cv2.imshow("composing_image", ret) - cv2.waitKey(0) - image_bytes = cv2.imencode(".jpg", ret)[1].tobytes() - image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}" - else: - image_bytes = cv2.imencode(".jpg", image['obj'])[1].tobytes() - image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}" + ''' 比例相同 整合上下装代码''' + image_width = image['obj'].shape[1] + waist_width = image['keypoint_result']['waistband_right'][1] - image['keypoint_result']['waistband_left'][1] + scale = 0.4 + if waist_width / scale >= image_width: + add_width = int((waist_width / scale - image_width) / 2) + ret = cv2.copyMakeBorder(image['obj'], 0, 0, add_width, add_width, cv2.BORDER_CONSTANT, value=(256, 256, 256)) + if IF_DEBUG_SHOW: + cv2.imshow("composing_image", ret) + cv2.waitKey(0) + image_bytes = cv2.imencode(".jpg", ret)[1].tobytes() + # image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}" + bucket_name = image['image_url'].split('/', 1)[0] + object_name = image['image_url'].split('/', 1)[1] + oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=image_bytes) + image['show_image_url'] = f"{bucket_name}/{object_name}" else: - scale = 0.4 - image_width = image['obj'].shape[1] - waist_width = image['keypoint_result']['armpit_right'][1] - image['keypoint_result']['armpit_left'][1] - if waist_width / scale >= image_width: - add_width = int((waist_width / scale - image_width) / 2) - ret = cv2.copyMakeBorder(image['obj'], 0, 0, add_width, add_width, cv2.BORDER_CONSTANT, value=(256, 256, 256)) - if IF_DEBUG_SHOW: - cv2.imshow("composing_image", ret) - cv2.waitKey(0) - image_bytes = cv2.imencode(".jpg", ret)[1].tobytes() - image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}" - else: - image_bytes = cv2.imencode(".jpg", image['obj'])[1].tobytes() - image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}" + image_bytes = cv2.imencode(".jpg", image['obj'])[1].tobytes() + # image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}" + bucket_name = image['image_url'].split('/', 1)[0] + object_name = image['image_url'].split('/', 1)[1] + oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=image_bytes) + image['show_image_url'] = f"{bucket_name}/{object_name}" + + # if image['site'] == 'down': + # image_width = image['obj'].shape[1] + # waist_width = image['keypoint_result']['waistband_right'][1] - image['keypoint_result']['waistband_left'][1] + # scale = 0.4 + # if waist_width / scale >= image_width: + # add_width = int((waist_width / scale - image_width) / 2) + # ret = cv2.copyMakeBorder(image['obj'], 0, 0, add_width, add_width, cv2.BORDER_CONSTANT, value=(256, 256, 256)) + # if IF_DEBUG_SHOW: + # cv2.imshow("composing_image", ret) + # cv2.waitKey(0) + # image_bytes = cv2.imencode(".jpg", ret)[1].tobytes() + # # image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}" + # bucket_name = image['image_url'].split('/', 1)[0] + # object_name = image['image_url'].split('/', 1)[1] + # oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=image_bytes) + # image['show_image_url'] = f"{bucket_name}/{object_name}" + # else: + # image_bytes = cv2.imencode(".jpg", image['obj'])[1].tobytes() + # # image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}" + # bucket_name = image['image_url'].split('/', 1)[0] + # object_name = image['image_url'].split('/', 1)[1] + # oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=image_bytes) + # image['show_image_url'] = f"{bucket_name}/{object_name}" + # else: + # image_width = image['obj'].shape[1] + # waist_width = image['keypoint_result']['waistband_right'][1] - image['keypoint_result']['waistband_left'][1] + # scale = 0.4 + # if waist_width / scale >= image_width: + # add_width = int((waist_width / scale - image_width) / 2) + # ret = cv2.copyMakeBorder(image['obj'], 0, 0, add_width, add_width, cv2.BORDER_CONSTANT, value=(256, 256, 256)) + # if IF_DEBUG_SHOW: + # cv2.imshow("composing_image", ret) + # cv2.waitKey(0) + # image_bytes = cv2.imencode(".jpg", ret)[1].tobytes() + # # image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}" + # bucket_name = image['image_url'].split('/', 1)[0] + # object_name = image['image_url'].split('/', 1)[1] + # oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=image_bytes) + # image['show_image_url'] = f"{bucket_name}/{object_name}" + # else: + # image_bytes = cv2.imencode(".jpg", image['obj'])[1].tobytes() + # # image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}" + # bucket_name = image['image_url'].split('/', 1)[0] + # object_name = image['image_url'].split('/', 1)[1] + # oss_upload_image(bucket=bucket_name, object_name=object_name, image_bytes=image_bytes) + # image['show_image_url'] = f"{bucket_name}/{object_name}" return image_list @staticmethod diff --git a/app/service/generate_image/service_generate_image.py b/app/service/generate_image/service_generate_image.py index 889aed7..d193de7 100644 --- a/app/service/generate_image/service_generate_image.py +++ b/app/service/generate_image/service_generate_image.py @@ -10,22 +10,17 @@ import json import logging import time -from io import BytesIO - import cv2 import minio import redis import tritonclient.grpc as grpcclient import numpy as np -from minio import Minio from tritonclient.utils import np_to_triton_dtype - from app.core.config import * from app.schemas.generate_image import GenerateImageModel -from app.service.generate_image.utils.adjust_contrast import adjust_contrast from app.service.generate_image.utils.image_processing import remove_background, stain_detection, generate_category_recognition, autoLevels, luminance_adjust, face_detect_pic -from app.service.generate_image.utils.upload_sd_image import upload_png_sd, upload_stain_png_sd -from app.service.utils.oss_client import get_image +from app.service.generate_image.utils.upload_sd_image import upload_png_sd +from app.service.utils.oss_client import oss_get_image logger = logging.getLogger() @@ -70,7 +65,7 @@ class GenerateImage: # image_cv2 = cv2.imdecode(image_array, cv2.IMREAD_COLOR) # image_rbg = cv2.cvtColor(image_cv2, cv2.COLOR_BGR2RGB) - image_cv2 = get_image(object_name=image_url, data_type="cv2") + image_cv2 = oss_get_image(bucket=image_url.split('/')[0], object_name=image_url, data_type="cv2") image_rbg = cv2.cvtColor(image_cv2, cv2.COLOR_BGR2RGB) image = cv2.resize(image_rbg, (1024, 1024)) except minio.error.S3Error: @@ -197,4 +192,4 @@ if __name__ == '__main__': gender="male" ) server = GenerateImage(rd) - print(server.get_result()) + print(server.get_result()) \ No newline at end of file diff --git a/app/service/super_resolution/service.py b/app/service/super_resolution/service.py index e87f1a7..f864d01 100644 --- a/app/service/super_resolution/service.py +++ b/app/service/super_resolution/service.py @@ -1,17 +1,15 @@ -import io +import json import logging import time -import minio.error -import redis -import json import cv2 +import minio.error import numpy as np +import redis import torch import tritonclient.grpc as grpcclient -from minio import Minio from app.core.config import * from app.schemas.super_resolution import SuperResolutionModel -from app.service.utils.decorator import RunTime +from app.service.utils.oss_client import oss_get_image, oss_upload_image logger = logging.getLogger() @@ -24,7 +22,7 @@ class SuperResolution: self.user_id = self.tasks_id[self.tasks_id.rfind('-') + 1:] self.sr_image_url = data.sr_image_url self.sr_xn = data.sr_xn - self.minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE) + # self.minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE) self.redis_client.set(self.tasks_id, json.dumps({'status': 'PENDING', 'message': "pending", 'data': ''})) self.redis_client.expire(self.tasks_id, 600) self.connection = pika.BlockingConnection(pika.ConnectionParameters(**RABBITMQ_PARAMS)) @@ -33,16 +31,25 @@ class SuperResolution: # @RunTime def read_image(self): try: - image_data = self.minio_client.get_object(self.sr_image_url.split("/", 1)[0], self.sr_image_url.split("/", 1)[1]) + img = oss_get_image(bucket=self.sr_image_url.split("/", 1)[0], object_name=self.sr_image_url.split("/", 1)[1], data_type="cv2") except minio.error.S3Error as e: sr_data = json.dumps({'tasks_id': self.tasks_id, 'status': 'ERROR', 'message': f'{e}'}) self.channel.basic_publish(exchange='', routing_key=SR_RABBITMQ_QUEUES, body=sr_data) logger.info(f" [x] Sent {sr_data}") raise FileNotFoundError(f"Image '{self.sr_image_url.split('/', 1)[1]}' not found in bucket '{self.sr_image_url.split('/', 1)[0]}'") - img = np.frombuffer(image_data.data, np.uint8) # 转成8位无符号整型 - img = cv2.imdecode(img, cv2.IMREAD_COLOR).astype(np.float32) / 255. # 解码 return img + # try: + # image_data = self.minio_client.get_object(self.sr_image_url.split("/", 1)[0], self.sr_image_url.split("/", 1)[1]) + # except minio.error.S3Error as e: + # sr_data = json.dumps({'tasks_id': self.tasks_id, 'status': 'ERROR', 'message': f'{e}'}) + # self.channel.basic_publish(exchange='', routing_key=SR_RABBITMQ_QUEUES, body=sr_data) + # logger.info(f" [x] Sent {sr_data}") + # raise FileNotFoundError(f"Image '{self.sr_image_url.split('/', 1)[1]}' not found in bucket '{self.sr_image_url.split('/', 1)[0]}'") + # img = np.frombuffer(image_data.data, np.uint8) # 转成8位无符号整型 + # img = cv2.imdecode(img, cv2.IMREAD_COLOR).astype(np.float32) / 255. # 解码 + # return img + def read_tasks_status(self): status_data = json.loads(self.redis_client.get(self.tasks_id)) logging.info(f"{self.tasks_id} ===> {status_data}") @@ -101,8 +108,10 @@ class SuperResolution: def upload_img_sr(self, image): try: image_bytes = cv2.imencode('.jpg', image)[1].tobytes() - res = self.minio_client.put_object(f'{SR_MINIO_BUCKET}', f'{self.user_id}/sr/output/{self.tasks_id}.jpg', io.BytesIO(image_bytes), len(image_bytes), content_type='image/png') - image_url = f"aida-users/{res.object_name}" + # res = self.minio_client.put_object(f'{SR_MINIO_BUCKET}', f'{self.user_id}/sr/output/{self.tasks_id}.jpg', io.BytesIO(image_bytes), len(image_bytes), content_type='image/png') + object_name = f'{self.user_id}/sr/output/{self.tasks_id}.jpg' + oss_upload_image(bucket=SR_MINIO_BUCKET, object_name=object_name, image_bytes=image_bytes) + image_url = f"{SR_MINIO_BUCKET}/{object_name}" return image_url except Exception as e: logger.warning(f"upload_png_mask runtime exception : {e}") diff --git a/app/service/utils/oss_client.py b/app/service/utils/oss_client.py index b2d3b7d..e293117 100644 --- a/app/service/utils/oss_client.py +++ b/app/service/utils/oss_client.py @@ -15,8 +15,8 @@ logger = logging.getLogger() # 获取图片 def oss_get_image(bucket, object_name, data_type): + # cv2 默认全通道读取 image_object = None - try: if OSS == "minio": oss_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE) @@ -24,11 +24,10 @@ def oss_get_image(bucket, object_name, data_type): else: oss_client = boto3.client('s3', aws_access_key_id=S3_ACCESS_KEY, aws_secret_access_key=S3_AWS_SECRET_ACCESS_KEY, region_name=S3_REGION_NAME) image_data = oss_client.get_object(Bucket=bucket, Key=object_name)['Body'] - if data_type == "cv2": image_bytes = image_data.read() image_array = np.frombuffer(image_bytes, np.uint8) # 转成8位无符号整型 - image_object = cv2.imdecode(image_array, cv2.IMREAD_COLOR) + image_object = cv2.imdecode(image_array, cv2.IMREAD_UNCHANGED) else: data_bytes = BytesIO(image_data.read()) image_object = Image.open(data_bytes) @@ -56,11 +55,12 @@ if __name__ == '__main__': # url = "aida-collection-element/11523/Moodboard/f60af0d2-94c2-48f9-90ff-74b8e8a481b5.jpg" # url = "aida-sys-image/images/female/outwear/0628000054.jpg" # url = "aida-users/89/product_image/string-89.png" - # url = "aida-users/89/single_logo/123-89.png" + url = "aida-users/89/single_logo/123-89.png" # url = 'aida-users/89/relight_image/123-89.png' # url = 'aida-users/89/relight_image/123-89.png' - url = 'aida-users/89/relight_image/123-89.png' - read_type = "PIL" + # url = 'aida-users/89/relight_image/123-89.png' + # url = "aida-users/89/sketchboard/female/Dress/e6724ab7-8d3f-4677-abe0-c3e42ab7af85.jpeg" + read_type = "cv2" if read_type == "cv2": img = oss_get_image(bucket=url.split('/')[0], object_name=url[url.find('/') + 1:], data_type=read_type) cv2.imshow("", img)