app

app.py

@@ -5,7 +5,7 @@ import subprocess
 subprocess.run(["bash", "setup.sh"])
 from segment_anything import SamPredictor, sam_model_registry
 from diffusers import StableDiffusionInpaintPipeline
-from groundingdino.util.inference import load_model, load_image, predict, annotate
+from GroundingDINO.groundingdino.util.inference import load_model, load_image, predict, annotate
 from GroundingDINO.groundingdino.util import box_ops
 from PIL import Image
 import torch
@@ -15,7 +15,7 @@ import os
 device = 'cuda'
 # ----SAM
 
-
+print("path", os.getcwd())
 # If weights are not present, download them.
 if not os.path.exists("./weights/sam_vit_h_4b8939.pth"):
     print("Downloading model weights...")
@@ -25,11 +25,11 @@ if not os.path.exists("./weights/groundingdino_swint_ogc.pth"):
     wget.download("https://github.com/IDEA-Research/GroundingDINO/releases/download/v0.1.0-alpha/groundingdino_swint_ogc.pth", out="./weights/groundingdino_swint_ogc.pth")
 
 model_type = "vit_h"
-predictor = SamPredictor(sam_model_registry[model_type](checkpoint="./GroundingDINO/weights/sam_vit_h_4b8939.pth").to(device="cuda"))
+predictor = SamPredictor(sam_model_registry[model_type](checkpoint="./weights/sam_vit_h_4b8939.pth").to(device="cuda"))
 # ------Stable Diffusion
 pipe = StableDiffusionInpaintPipeline.from_pretrained("stabilityai/stable-diffusion-2-inpainting", torch_dtype=torch.float16,).to(device)
 # ----Grounding DINO
-groundingdino_model = load_model("./GroundingDINO/groundingdino/config/GroundingDINO_SwinT_OGC.py", "./GroundingDINO/weights/groundingdino_swint_ogc.pth")
+groundingdino_model = load_model("./groundingdino/config/GroundingDINO_SwinT_OGC.py", "./weights/groundingdino_swint_ogc.pth")
 
 BOX_TRESHOLD = 0.3
 TEXT_TRESHOLD = 0.25

setup.sh

@@ -21,6 +21,5 @@ wget https://github.com/IDEA-Research/GroundingDINO/releases/download/v0.1.0-alp
 
 # Change directory back to the project root
 cd ..
-cd GroundingDINO
 pwd
 ls