feat generate img fast version 部署

fix

app/core/config.py

@@ -101,6 +101,7 @@ SR_RABBITMQ_QUEUES = os.getenv("SR_RABBITMQ_QUEUES", f"SuperResolution{RABBITMQ_
 
 # GenerateImage service config
 GI_MODEL_NAME = 'stable_diffusion_xl'
+FAST_GI_MODEL_URL = '10.1.1.243:10011'
 GI_MODEL_URL = '10.1.1.240:10041'
 GI_MINIO_BUCKET = "aida-users"
 GI_RABBITMQ_QUEUES = os.getenv("GI_RABBITMQ_QUEUES", f"GenerateImage{RABBITMQ_ENV}")

app/schemas/generate_image.py

@@ -8,6 +8,7 @@ class GenerateImageModel(BaseModel):
     mode: str
     category: str
     gender: str
+    version: str
 
 
 class GenerateSingleLogoImageModel(BaseModel):

app/service/generate_image/service_generate_image.py

@@ -35,7 +35,11 @@ class GenerateImage:
         # 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=GI_MODEL_URL)
+        if request_data.version == "fast":
+            self.grpc_client = grpcclient.InferenceServerClient(url=FAST_GI_MODEL_URL)
+        else:
+            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":
             # cv2 读图片是BGR PIL读图片是RGB
@@ -185,7 +189,8 @@ if __name__ == '__main__':
         image_url="aida-collection-element/87/Printboard/842c09cf-7297-42d9-9e6e-9c17d4a13cb5.jpg",
         mode='txt2img',
         category="test",
-        gender="male"
+        gender="male",
+        version="fast"
     )
     server = GenerateImage(rd)
     print(server.get_result())

app/service/generate_image/service_generate_product_image.py

@@ -55,7 +55,10 @@ class GenerateProductImage:
             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")
+            if self.product_type == "single":
+                image = result.as_numpy("generated_inpaint_image")
+            else:
+                image = result.as_numpy("generated_cnet_image")
             image_result = Image.fromarray(np.squeeze(image.astype(np.uint8))).resize(self.image_size)
             cropped_image = post_processing_image(image_result, self.left, self.top)
             image_url = upload_SDXL_image(cropped_image, user_id=self.user_id, category=f"{self.category}", file_name=f"{self.tasks_id}.png")
@@ -75,9 +78,14 @@ class GenerateProductImage:
             self.image = cv2.resize(self.image, (1024, 1024))
             images = [self.image.astype(np.uint8)] * self.batch_size
 
-            text_obj = np.array(prompts, dtype="object").reshape((1))
-            image_obj = np.array(images, dtype=np.uint8).reshape((1024, 1024, 3))
-            image_strength_obj = np.array(self.image_strength, dtype=np.float32).reshape((1))
+            if self.product_type == "single":
+                text_obj = np.array(prompts, dtype="object").reshape(-1, 1)
+                image_obj = np.array(images, dtype=np.uint8).reshape((-1, 1024, 1024, 3))
+                image_strength_obj = np.array(self.image_strength, dtype=np.float32).reshape(-1, 1)
+            else:
+                text_obj = np.array(prompts, dtype="object").reshape((1))
+                image_obj = np.array(images, dtype=np.uint8).reshape((1024, 1024, 3))
+                image_strength_obj = np.array(self.image_strength, dtype=np.float32).reshape((1))
 
             # 假设 prompts、images 和 self.image_strength 已经定义
 
@@ -91,7 +99,11 @@ class GenerateProductImage:
 
             inputs = [input_text, input_image, input_image_strength]
 
-            ctx = self.grpc_client.async_infer(model_name=GPI_MODEL_NAME_OVERALL, inputs=inputs, callback=self.callback)
+
+            if self.product_type == "single":
+                ctx = self.grpc_client.async_infer(model_name="stable_diffusion_xl_cnet_inpaint", inputs=inputs, callback=self.callback)
+            else:
+                ctx = self.grpc_client.async_infer(model_name=GPI_MODEL_NAME_OVERALL, inputs=inputs, callback=self.callback)
 
             time_out = 600
             while time_out > 0:
@@ -173,10 +185,10 @@ if __name__ == '__main__':
     rd = GenerateProductImageModel(
         tasks_id="123-89",
         # prompt="",
-        image_strength=0.65,
-        prompt="The best quality, masterpiece, real image. A handsome man wearing blouse, outwear, trousers, 8K realistic, HUD",
-        image_url="aida-results/result_00097282-ebb2-11ee-a822-b48351119060.png",
-        product_type="overall"
+        image_strength=0.7,
+        prompt="The best quality, masterpiece,outwear, 8K realistic, HUD",
+        image_url="aida-results/result_836dce70-ad59-11ef-86ab-0242ac130002.png",
+        product_type="single"
     )
     server = GenerateProductImage(rd)
-    print(server.get_result())
+    print(server.get_result())

app/service/utils/new_oss_client.py

@@ -82,7 +82,7 @@ if __name__ == '__main__':
     # url = "aida-users/89/sketchboard/female/Dress/e6724ab7-8d3f-4677-abe0-c3e42ab7af85.jpeg"
     # url = "aida-users/87/print/956614a2-7e75-4fbe-9ed0-c1831e37a2c9-4-87.png"
     # url = "aida-users/89/single_logo/123-89.png"
-    url ="aida-results/result_00097282-ebb2-11ee-a822-b48351119060.png"
+    url ="aida-users/89/test/123-89.png"
 
     # url = "aida-collection-element/12148/Sketchboard/95ea577b-305b-4a62-b30a-39c0dd3ddb3f.png"
     read_type = "2"