chore: Add inpainting and outpainting router to product diffusion API

product_diffusion_api/endpoints.py

@@ -1,7 +1,7 @@
 from fastapi import FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from routers import sdxl_text_to_image
-
+from routers import painting
 
 
 
@@ -16,6 +16,8 @@ app.add_middleware(
 )
 
 app.include_router(sdxl_text_to_image.router, prefix='/api/v1/product-diffusion')
+app.include_router(painting.router,prefix='/api/v1/product-diffusion')
+
 
 
 

product_diffusion_api/routers/painting.py

@@ -0,0 +1,7 @@
+from fastapi import APIRouter, HTTPException
+
+
+
+
+
+router = APIRouter()

product_diffusion_api/routers/sdxl_text_to_image.py

@@ -231,6 +231,7 @@ async def sdxl_v0_lora_inference_batch(data: BatchInputFormat):
             item.num_images,
             item.num_inference_steps,
             item.guidance_scale,
+            item.mode,
         )
         output_json = inference.run_inference()
         processed_requests.append(output_json)

scripts/config.py

@@ -3,6 +3,8 @@ ADAPTER_NAME = "VikramSingh178/sdxl-lora-finetune-product-caption"
 VAE_NAME= "madebyollin/sdxl-vae-fp16-fix"
 DATASET_NAME= "hahminlew/kream-product-blip-captions"
 PROJECT_NAME = "Product Photography"
+PRODUCTS_10k_DATASET = "amaye15/Products-10k"
+
 
 class Config:
     def __init__(self):

scripts/products10k_captions.py

@@ -0,0 +1,18 @@
+from datasets import load_dataset
+from config import PRODUCTS_10k_DATASET
+from transformers import BlipProcessor, BlipForConditionalGeneration
+from tqdm import tqdm
+import torch
+
+
+device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+dataset = load_dataset(PRODUCTS_10k_DATASET)
+
+
+def image_captioning(processor , )
+
+
+
+
+
+