diff --git a/app/core/config.py b/app/core/config.py index b574845..4e74711 100644 --- a/app/core/config.py +++ b/app/core/config.py @@ -19,6 +19,7 @@ class Settings(BaseSettings): LOGGING_CONFIG_FILE = os.path.join(BASE_DIR, 'logging_env.py') +OSS = "minio" DEBUG = False if DEBUG: LOGS_PATH = "logs/" @@ -47,7 +48,7 @@ S3_AWS_SECRET_ACCESS_KEY = "LNIwFFB27/QedtZ+Q/viVUoX9F5x1DbuM8N0DkD8" S3_REGION_NAME = "ap-east-1" # redis 配置 -REDIS_HOST = "10.1.1.240" +REDIS_HOST = "10.1.1.150" REDIS_PORT = "6379" REDIS_DB = "2" @@ -120,7 +121,8 @@ GEN_SINGLE_LOGO_RABBITMQ_QUEUES = os.getenv("GEN_SINGLE_LOGO_RABBITMQ_QUEUES", f # Generate Single Logo service config GPI_RABBITMQ_QUEUES = os.getenv("GEN_PRODUCT_IMAGE_RABBITMQ_QUEUES", f"ToProductImage{RABBITMQ_ENV}") GPI_MODEL_NAME = 'diffusion_ensemble_all' -GPI_MODEL_URL = '10.1.1.240:10061' +# GPI_MODEL_URL = '10.1.1.240:10061' +GPI_MODEL_URL = '10.1.1.150:8001' # Generate Single Logo service config GRI_RABBITMQ_QUEUES = os.getenv("GEN_RELIGHT_IMAGE_RABBITMQ_QUEUES", f"Relight{RABBITMQ_ENV}") diff --git a/app/service/generate_image/service_generate_image.py b/app/service/generate_image/service_generate_image.py index 6f8d092..889aed7 100644 --- a/app/service/generate_image/service_generate_image.py +++ b/app/service/generate_image/service_generate_image.py @@ -25,6 +25,7 @@ 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 logger = logging.getLogger() @@ -36,7 +37,7 @@ class GenerateImage: self.channel = self.connection.channel() # self.connection = pika.BlockingConnection(pika.ConnectionParameters(**RABBITMQ_PARAMS)) # self.channel = self.connection.channel() - 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.grpc_client = grpcclient.InferenceServerClient(url=GI_MODEL_URL) self.redis_client = redis.StrictRedis(host=REDIS_HOST, port=REDIS_PORT, db=REDIS_DB, decode_responses=True) if request_data.mode == "img2img": @@ -63,10 +64,13 @@ class GenerateImage: # Read data from response. # read image use cv2 try: - response = self.minio_client.get_object(image_url.split('/')[0], image_url[image_url.find('/') + 1:]) - image_file = BytesIO(response.data) - image_array = np.asarray(bytearray(image_file.read()), dtype=np.uint8) - image_cv2 = cv2.imdecode(image_array, cv2.IMREAD_COLOR) + # response = self.minio_client.get_object(image_url.split('/')[0], image_url[image_url.find('/') + 1:]) + # image_file = BytesIO(response.data) + # image_array = np.asarray(bytearray(image_file.read()), dtype=np.uint8) + # 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_rbg = cv2.cvtColor(image_cv2, cv2.COLOR_BGR2RGB) image = cv2.resize(image_rbg, (1024, 1024)) except minio.error.S3Error: @@ -189,7 +193,8 @@ if __name__ == '__main__': prompt='skeleton sitting by the side of a river looking soulful, concert poster, 4k, artistic', image_url="", mode='txt2img', - category="test" + category="test", + gender="male" ) server = GenerateImage(rd) print(server.get_result()) diff --git a/app/service/generate_image/service_generate_product_image.py b/app/service/generate_image/service_generate_product_image.py index 2416d2c..dcdf09f 100644 --- a/app/service/generate_image/service_generate_product_image.py +++ b/app/service/generate_image/service_generate_product_image.py @@ -18,10 +18,10 @@ import numpy as np from PIL import Image, ImageOps from minio import Minio from tritonclient.utils import np_to_triton_dtype - from app.core.config import * -from app.schemas.generate_image import GenerateImageModel, GenerateProductImageModel +from app.schemas.generate_image import GenerateProductImageModel from app.service.generate_image.utils.upload_sd_image import upload_SDXL_image +from app.service.utils.oss_client import oss_get_image logger = logging.getLogger() @@ -33,69 +33,29 @@ class GenerateProductImage: self.channel = self.connection.channel() # self.connection = pika.BlockingConnection(pika.ConnectionParameters(**RABBITMQ_PARAMS)) # self.channel = self.connection.channel() - 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.grpc_client = grpcclient.InferenceServerClient(url=GPI_MODEL_URL) self.redis_client = redis.StrictRedis(host=REDIS_HOST, port=REDIS_PORT, db=REDIS_DB, decode_responses=True) self.category = "product_image" self.batch_size = 1 self.prompt = request_data.prompt - # TODO aida design 结果图背景改为白色 - self.image, self.image_size = self.get_image(request_data.image_url) - # TODO image 填充并resize成512*768 - + self.image, self.image_size = pre_processing_image(request_data.image_url) self.tasks_id = request_data.tasks_id self.user_id = self.tasks_id[self.tasks_id.rfind('-') + 1:] self.gen_product_data = {'tasks_id': self.tasks_id, 'status': 'PENDING', 'message': "pending", 'image_url': ''} self.redis_client.set(self.tasks_id, json.dumps(self.gen_product_data)) self.redis_client.expire(self.tasks_id, 600) - def get_image(self, image_url): - response = self.minio_client.get_object(image_url.split('/')[0], image_url[image_url.find('/') + 1:]) - image_bytes = io.BytesIO(response.read()) - - # 转换为PIL图像对象 - image = Image.open(image_bytes) - target_height = 768 - target_width = 512 - - aspect_ratio = image.width / image.height - new_width = int(target_height * aspect_ratio) - - resized_image = image.resize((new_width, target_height)) - left = (target_width - resized_image.width) // 2 - top = (target_height - resized_image.height) // 2 - right = target_width - resized_image.width - left - bottom = target_height - resized_image.height - top - image = ImageOps.expand(resized_image, (left, top, right, bottom), fill="white") - image_size = image.size - if image.mode in ('RGBA', 'LA') or (image.mode == 'P' and 'transparency' in image.info): - # 创建白色背景 - background = Image.new("RGB", image.size, (255, 255, 255)) - # 将图片粘贴到白色背景上 - background.paste(image, mask=image.split()[3]) - image = np.array(background) - image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) - - # image_file = BytesIO(response.data) - # image_array = np.asarray(bytearray(image_file.read()), dtype=np.uint8) - # image_cv2 = cv2.imdecode(image_array, cv2.IMREAD_COLOR) - # image = cv2.cvtColor(image_cv2, cv2.COLOR_BGR2RGB) - # image = cv2.resize(image_rbg, (1024, 1024)) - return image, image_size - def callback(self, result, error): if error: self.gen_product_data['status'] = "FAILURE" self.gen_product_data['message'] = str(error) - # self.gen_product_data['data'] = str(error) self.redis_client.set(self.tasks_id, json.dumps(self.gen_product_data)) else: # pil图像转成numpy数组 image = result.as_numpy("generated_inpaint_image") image_result = Image.fromarray(np.squeeze(image.astype(np.uint8))).resize(self.image_size) - - image_url = upload_SDXL_image(image_result, user_id=self.user_id, category=f"{self.category}", object_name=f"{self.tasks_id}.png") - # logger.info(f"upload image SUCCESS ： {image_url}") + image_url = upload_SDXL_image(image_result, user_id=self.user_id, category=f"{self.category}", file_name=f"{self.tasks_id}.png") self.gen_product_data['status'] = "SUCCESS" self.gen_product_data['message'] = "success" self.gen_product_data['image_url'] = str(image_url) @@ -105,13 +65,6 @@ class GenerateProductImage: status_data = self.redis_client.get(self.tasks_id) return json.loads(status_data), status_data - def infer(self, inputs): - return self.grpc_client.async_infer( - model_name=GPI_MODEL_NAME, - inputs=inputs, - callback=self.callback - ) - def get_result(self): try: prompts = [self.prompt] * self.batch_size @@ -129,11 +82,10 @@ class GenerateProductImage: input_image.set_data_from_numpy(image_obj) inputs = [input_text, input_image] - ctx = self.infer(inputs) + ctx = self.grpc_client.async_infer(model_name=GPI_MODEL_NAME, inputs=inputs, callback=self.callback) time_out = 600 while time_out > 0: gen_product_data, _ = self.read_tasks_status() - # logger.info(gen_product_data) if gen_product_data['status'] in ["REVOKED", "FAILURE"]: ctx.cancel() break @@ -141,7 +93,6 @@ class GenerateProductImage: break time_out -= 1 time.sleep(0.1) - # logger.info(time_out, gen_product_data) gen_product_data, _ = self.read_tasks_status() return gen_product_data except Exception as e: @@ -153,7 +104,6 @@ class GenerateProductImage: dict_gen_product_data, str_gen_product_data = self.read_tasks_status() if DEBUG is False: self.channel.basic_publish(exchange='', routing_key=GPI_RABBITMQ_QUEUES, body=str_gen_product_data) - # self.channel.basic_publish(exchange='', routing_key=GEN_PRODUCT_IMAGE_RABBITMQ_QUEUES, body=str_gen_product_data) logger.info(f" [x] Sent to： {GPI_RABBITMQ_QUEUES} data：@@@@ {json.dumps(dict_gen_product_data, indent=4)}") @@ -165,11 +115,36 @@ def infer_cancel(tasks_id): return data +def pre_processing_image(image_url): + image = oss_get_image(bucket=image_url.split('/')[0], object_name=image_url[image_url.find('/') + 1:], data_type="PIL") + + # resize 图片内尺寸 并贴到768-512的纯白图像上 + target_height = 768 + target_width = 512 + aspect_ratio = image.width / image.height + new_width = int(target_height * aspect_ratio) + resized_image = image.resize((new_width, target_height)) + left = (target_width - resized_image.width) // 2 + top = (target_height - resized_image.height) // 2 + right = target_width - resized_image.width - left + bottom = target_height - resized_image.height - top + image = ImageOps.expand(resized_image, (left, top, right, bottom), fill="white") + image_size = image.size + if image.mode in ('RGBA', 'LA') or (image.mode == 'P' and 'transparency' in image.info): + # 创建白色背景 + background = Image.new("RGB", image.size, (255, 255, 255)) + # 将图片粘贴到白色背景上 + background.paste(image, mask=image.split()[3]) + image = np.array(background) + image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) + return image, image_size + + if __name__ == '__main__': rd = GenerateProductImageModel( tasks_id="123-89", prompt="", - # prompt="best quality, masterpiece. detailed, high-res, simple background, studio photography, extremely detailed, updo, detailed face, face, close-up, HDR, UHD, 8K realistic, Highly detailed, simple background, Studio lighting", + # prompt=" the best quality, masterpiece. detailed, high-res, simple background, studio photography, extremely detailed, updo, detailed face, face, close-up, HDR, UHD, 8K realistic, Highly detailed, simple background, Studio lighting", image_url="aida-results/result_00097282-ebb2-11ee-a822-b48351119060.png", ) server = GenerateProductImage(rd) diff --git a/app/service/generate_image/service_generate_relight_image.py b/app/service/generate_image/service_generate_relight_image.py index 7c7f4b1..8793c42 100644 --- a/app/service/generate_image/service_generate_relight_image.py +++ b/app/service/generate_image/service_generate_relight_image.py @@ -22,6 +22,7 @@ from tritonclient.utils import np_to_triton_dtype from app.core.config import * from app.schemas.generate_image import GenerateRelightImageModel from app.service.generate_image.utils.upload_sd_image import upload_SDXL_image +from app.service.utils.oss_client import oss_get_image logger = logging.getLogger() @@ -31,43 +32,34 @@ class GenerateRelightImage: if DEBUG is False: self.connection = pika.BlockingConnection(pika.ConnectionParameters(**RABBITMQ_PARAMS)) self.channel = self.connection.channel() - 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.grpc_client = grpcclient.InferenceServerClient(url=GRI_MODEL_URL) self.redis_client = redis.StrictRedis(host=REDIS_HOST, port=REDIS_PORT, db=REDIS_DB, decode_responses=True) self.category = "relight_image" self.batch_size = 1 self.prompt = request_data.prompt - self.seed = "12345" + self.seed = "1" self.negative_prompt = 'lowres, bad anatomy, bad hands, cropped, worst quality' self.direction = "Right Light" - # TODO aida design 结果图背景改为白色 - self.image = self.get_image(request_data.image_url) - # TODO image 填充并resize成512*768 - + self.image_url = request_data.image_url + self.image = oss_get_image(bucket=self.image_url.split('/')[0], object_name=self.image_url[self.image_url.find('/') + 1:], data_type="cv2") self.tasks_id = request_data.tasks_id self.user_id = self.tasks_id[self.tasks_id.rfind('-') + 1:] self.gen_product_data = {'tasks_id': self.tasks_id, 'status': 'PENDING', 'message': "pending", 'image_url': ''} self.redis_client.set(self.tasks_id, json.dumps(self.gen_product_data)) self.redis_client.expire(self.tasks_id, 600) - def get_image(self, image_url): - response = self.minio_client.get_object(image_url.split('/')[0], image_url[image_url.find('/') + 1:]) - image = cv2.imdecode(np.frombuffer(response.data, np.uint8), 1) - return image - def callback(self, result, error): if error: self.gen_product_data['status'] = "FAILURE" self.gen_product_data['message'] = str(error) - # self.gen_product_data['data'] = str(error) self.redis_client.set(self.tasks_id, json.dumps(self.gen_product_data)) else: # pil图像转成numpy数组 image = result.as_numpy("generated_inpaint_image") image_result = Image.fromarray(np.squeeze(image.astype(np.uint8))) - image_url = upload_SDXL_image(image_result, user_id=self.user_id, category=f"{self.category}", object_name=f"{self.tasks_id}.png") - # logger.info(f"upload image SUCCESS ： {image_url}") + image_url = upload_SDXL_image(image_result, user_id=self.user_id, category=f"{self.category}", file_name=f"{self.tasks_id}.png") self.gen_product_data['status'] = "SUCCESS" self.gen_product_data['message'] = "success" self.gen_product_data['image_url'] = str(image_url) @@ -77,13 +69,6 @@ class GenerateRelightImage: status_data = self.redis_client.get(self.tasks_id) return json.loads(status_data), status_data - def infer(self, inputs): - return self.grpc_client.async_infer( - model_name=GRI_MODEL_NAME, - inputs=inputs, - callback=self.callback - ) - def get_result(self): try: prompts = [self.prompt] * self.batch_size @@ -114,11 +99,10 @@ class GenerateRelightImage: inputs = [input_text, input_natext, input_image, input_seed, input_direction] - ctx = self.infer(inputs) + ctx = self.grpc_client.async_infer(model_name=GRI_MODEL_NAME, inputs=inputs, callback=self.callback) time_out = 600 while time_out > 0: gen_product_data, _ = self.read_tasks_status() - # logger.info(gen_product_data) if gen_product_data['status'] in ["REVOKED", "FAILURE"]: ctx.cancel() break @@ -126,7 +110,6 @@ class GenerateRelightImage: break time_out -= 1 time.sleep(0.1) - # logger.info(time_out, gen_product_data) gen_product_data, _ = self.read_tasks_status() return gen_product_data except Exception as e: @@ -138,7 +121,6 @@ class GenerateRelightImage: dict_gen_product_data, str_gen_product_data = self.read_tasks_status() if DEBUG is False: self.channel.basic_publish(exchange='', routing_key=GRI_RABBITMQ_QUEUES, body=str_gen_product_data) - # self.channel.basic_publish(exchange='', routing_key=GEN_PRODUCT_IMAGE_RABBITMQ_QUEUES, body=str_gen_product_data) logger.info(f" [x] Sent to： {GRI_RABBITMQ_QUEUES} data：@@@@ {json.dumps(dict_gen_product_data, indent=4)}") @@ -154,7 +136,7 @@ if __name__ == '__main__': rd = GenerateRelightImageModel( tasks_id="123-89", # prompt="beautiful woman, detailed face, sunshine, outdoor, warm atmosphere", - prompt="", + prompt="Colorful black", image_url='aida-users/89/product_image/123-89.png' ) server = GenerateRelightImage(rd) diff --git a/app/service/generate_image/service_generate_single_logo.py b/app/service/generate_image/service_generate_single_logo.py index f3d1719..e3def3e 100644 --- a/app/service/generate_image/service_generate_single_logo.py +++ b/app/service/generate_image/service_generate_single_logo.py @@ -31,8 +31,6 @@ class GenerateSingleLogoImage: if DEBUG is False: self.connection = pika.BlockingConnection(pika.ConnectionParameters(**RABBITMQ_PARAMS)) self.channel = self.connection.channel() - # self.connection = pika.BlockingConnection(pika.ConnectionParameters(**RABBITMQ_PARAMS)) - # self.channel = self.connection.channel() self.minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE) self.grpc_client = grpcclient.InferenceServerClient(url=GSL_MODEL_URL) self.redis_client = redis.StrictRedis(host=REDIS_HOST, port=REDIS_PORT, db=REDIS_DB, decode_responses=True) @@ -51,23 +49,15 @@ class GenerateSingleLogoImage: status_data = self.redis_client.get(self.tasks_id) return json.loads(status_data), status_data - def infer(self, inputs): - return self.grpc_client.async_infer( - model_name=GSL_MODEL_NAME, - inputs=inputs, - callback=self.callback - ) - def callback(self, result, error): if error: self.gen_single_logo_data['status'] = "FAILURE" self.gen_single_logo_data['message'] = str(error) - # self.generate_data['data'] = str(error) self.redis_client.set(self.tasks_id, json.dumps(self.gen_single_logo_data)) else: image = result.as_numpy("generated_image") image_result = Image.fromarray(np.squeeze(image.astype(np.uint8))) - image_url = upload_SDXL_image(image_result, user_id=self.user_id, category=f"{self.category}", object_name=f"{self.tasks_id}.png") + image_url = upload_SDXL_image(image_result, user_id=self.user_id, category=f"{self.category}", file_name=f"{self.tasks_id}.png") self.gen_single_logo_data['status'] = "SUCCESS" self.gen_single_logo_data['message'] = "success" self.gen_single_logo_data['image_url'] = str(image_url) @@ -81,25 +71,19 @@ class GenerateSingleLogoImage: input_text = grpcclient.InferInput("prompt", text_obj.shape, np_to_triton_dtype(text_obj.dtype)) input_text.set_data_from_numpy(text_obj) - # negative_prompts text_obj_neg = np.array(self.negative_prompts, dtype="object").reshape((-1, 1)) - # print('text obj neg: ', text_obj_neg) input_text_neg = grpcclient.InferInput("negative_prompt", text_obj_neg.shape, np_to_triton_dtype(text_obj_neg.dtype)) input_text_neg.set_data_from_numpy(text_obj_neg) - # seed seed = np.array(self.seed, dtype="object").reshape((-1, 1)) input_seed = grpcclient.InferInput("seed", seed.shape, np_to_triton_dtype(seed.dtype)) input_seed.set_data_from_numpy(seed) - inputs = [input_text, input_text_neg, input_seed] - - ctx = self.infer(inputs) + ctx = self.grpc_client.async_infer(model_name=GSL_MODEL_NAME, inputs=inputs, callback=self.callback) time_out = 600 generate_data = None while time_out > 0: generate_data, _ = self.read_tasks_status() - # logger.info(generate_data) if generate_data['status'] in ["REVOKED", "FAILURE"]: ctx.cancel() break @@ -107,7 +91,6 @@ class GenerateSingleLogoImage: break time_out -= 1 time.sleep(0.1) - # logger.info(time_out, generate_data) return generate_data except Exception as e: raise Exception(str(e)) @@ -115,7 +98,6 @@ class GenerateSingleLogoImage: dict_generate_data, str_generate_data = self.read_tasks_status() if DEBUG is False: self.channel.basic_publish(exchange='', routing_key=GI_RABBITMQ_QUEUES, body=str_generate_data) - # self.channel.basic_publish(exchange='', routing_key=GI_RABBITMQ_QUEUES, body=str_generate_data) logger.info(f" [x] Sent {json.dumps(dict_generate_data, indent=4)}") diff --git a/app/service/generate_image/utils/upload_sd_image.py b/app/service/generate_image/utils/upload_sd_image.py index ec476f9..a63488c 100644 --- a/app/service/generate_image/utils/upload_sd_image.py +++ b/app/service/generate_image/utils/upload_sd_image.py @@ -16,8 +16,11 @@ from PIL import Image from minio import Minio from app.core.config import * +from app.service.utils.oss_client import oss_upload_image 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) @@ -34,36 +37,34 @@ minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET # except Exception as e: # print(f'上传到 S3 失败: {e}') -def upload_SDXL_image(image, user_id, category, object_name): +def upload_SDXL_image(image, user_id, category, file_name): try: image_data = io.BytesIO() image.save(image_data, format='PNG') image_data.seek(0) image_bytes = image_data.read() - minio_req = minio_client.put_object( - GI_MINIO_BUCKET, - f'{user_id}/{category}/{object_name}', - io.BytesIO(image_bytes), - len(image_bytes), - content_type='image/jpeg' - ) - image_url = f"aida-users/{minio_req.object_name}" + + # minio_req = minio_client.put_object( + # GI_MINIO_BUCKET, + # f'{user_id}/{category}/{file_name}', + # io.BytesIO(image_bytes), + # len(image_bytes), + # content_type='image/jpeg' + # ) + object_name = f'{user_id}/{category}/{file_name}' + req = oss_upload_image(bucket=GI_MINIO_BUCKET, object_name=object_name, image_bytes=image_bytes) + image_url = f"aida-users/{object_name}" return image_url except Exception as e: logging.warning(f"upload_png_mask runtime exception : {e}") -def upload_png_sd(image, user_id, category, object_name): +def upload_png_sd(image, user_id, category, file_name): try: _, img_byte_array = cv2.imencode('.jpg', image) - minio_req = minio_client.put_object( - GI_MINIO_BUCKET, - f'{user_id}/{category}/{object_name}', - io.BytesIO(img_byte_array), - len(img_byte_array), - content_type='image/jpeg' - ) - image_url = f"aida-users/{minio_req.object_name}" + object_name = f'{user_id}/{category}/{file_name}' + req = oss_upload_image(bucket=GI_MINIO_BUCKET, object_name=object_name, image_bytes=img_byte_array) + image_url = f"aida-users/{object_name}" return image_url except Exception as e: logging.warning(f"upload_png_mask runtime exception : {e}") diff --git a/app/service/utils/oss_client.py b/app/service/utils/oss_client.py new file mode 100644 index 0000000..b2d3b7d --- /dev/null +++ b/app/service/utils/oss_client.py @@ -0,0 +1,70 @@ +import io +import logging +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 * + +logger = logging.getLogger() + + +# 获取图片 +def oss_get_image(bucket, object_name, data_type): + image_object = None + + try: + if OSS == "minio": + oss_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE) + image_data = oss_client.get_object(bucket_name=bucket, object_name=object_name) + 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) + else: + data_bytes = BytesIO(image_data.read()) + image_object = Image.open(data_bytes) + except Exception as e: + logger.warning(f"{OSS} | 获取图片出现异常 ######: {e}") + return image_object + + +def oss_upload_image(bucket, object_name, image_bytes): + req = None + try: + if OSS == "minio": + oss_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE) + req = oss_client.put_object(bucket_name=bucket, object_name=object_name, data=io.BytesIO(image_bytes), length=len(image_bytes), content_type='image/png') + 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) + req = oss_client.put_object(Bucket=AIDA_CLOTHING, Key=object_name, Body=image_bytes, ContentType='image/png') + except Exception as e: + logger.warning(f"{OSS} | 上传图片出现异常 ######: {e}") + return req + + +if __name__ == '__main__': + # url = "aida-results/result_0002186a-e631-11ee-86a6-b48351119060.png" + # 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/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" + 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) + cv2.waitKey(0) + else: + img = oss_get_image(bucket=url.split('/')[0], object_name=url[url.find('/') + 1:], data_type=read_type) + img.show()