initial commit

app.py

@@ -1,29 +0,0 @@
-from _typeshed import OpenBinaryModeUpdating
-from types import resolve_bases
-import requests
-import gradio as gr
-import torch
-from timm import create_model
-from tim.data import reslove_data_config
-from timm.data.transformer import create_transform
-
-IMAGENET_1k_URL = "https://storage.googleapis.com/bit_models/ilsvrc2012_wordnet_lemmas.txt"
-LABELS = requests.get(IMAGENET_1k_URL).text.strip().split('\n')
-
-model = create_model('restnet50',pretrained=True)
-
-transofrm = create_transform(**resolve_data_config{}, model=model)
-
-model.eval()
-
-def predict_fn(img):
-    img = img.convert('RGB')
-    img = transofrm(img).unsqueez(0)
-
-    with torch.no_grad():
-        out = model(img)
-    probabilites = torch.nn.functional.softmax(out[0], dim=0)
-
-    values , indices = torch.topk(probabilites, k=5)
-
-    # return