Spaces:
Sleeping
Sleeping
Commit
·
9bfd721
1
Parent(s):
2d42726
model files are moved to hf from gdrive due to the download limit error
Browse files
app.py
CHANGED
@@ -8,9 +8,20 @@ import utils
|
|
8 |
from ldm.util import instantiate_from_config
|
9 |
from omegaconf import OmegaConf
|
10 |
from zipfile import ZipFile
|
11 |
-
import gdown
|
12 |
import os
|
|
|
|
|
13 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
14 |
MODEL = None
|
15 |
|
16 |
def inference(image: np.ndarray, instruction: str, center_crop: bool):
|
@@ -37,11 +48,11 @@ if __name__ == "__main__":
|
|
37 |
)
|
38 |
args = parser.parse_args()
|
39 |
|
40 |
-
|
41 |
-
|
42 |
-
|
43 |
-
|
44 |
-
|
45 |
parsed_config = OmegaConf.load(args.config)
|
46 |
MODEL = instantiate_from_config(parsed_config["model"])
|
47 |
model_state_dict = torch.load(args.checkpoint, map_location="cpu")["state_dict"]
|
|
|
8 |
from ldm.util import instantiate_from_config
|
9 |
from omegaconf import OmegaConf
|
10 |
from zipfile import ZipFile
|
|
|
11 |
import os
|
12 |
+
import requests
|
13 |
+
import shutil
|
14 |
|
15 |
+
def download_model(url):
|
16 |
+
os.makedirs("models", exist_ok=True)
|
17 |
+
local_filename = url.split('/')[-1]
|
18 |
+
with requests.get(url, stream=True) as r:
|
19 |
+
with open(os.path.join("models", local_filename), 'wb') as file:
|
20 |
+
shutil.copyfileobj(r.raw, file)
|
21 |
+
with ZipFile("models/gqa_inpaint.zip", 'r') as zObject:
|
22 |
+
zObject.extractall(path="models/")
|
23 |
+
os.remove("models/gqa_inpaint.zip")
|
24 |
+
|
25 |
MODEL = None
|
26 |
|
27 |
def inference(image: np.ndarray, instruction: str, center_crop: bool):
|
|
|
48 |
)
|
49 |
args = parser.parse_args()
|
50 |
|
51 |
+
print("## Downloading the model file")
|
52 |
+
download_model("https://huggingface.co/abyildirim/inst-inpaint-models/resolve/main/gqa_inpaint.zip")
|
53 |
+
print("## Download is completed")
|
54 |
+
|
55 |
+
print("## Running the demo")
|
56 |
parsed_config = OmegaConf.load(args.config)
|
57 |
MODEL = instantiate_from_config(parsed_config["model"])
|
58 |
model_state_dict = torch.load(args.checkpoint, map_location="cpu")["state_dict"]
|