added model

app.py

@@ -0,0 +1,28 @@
+import requests
+import gradio as gr
+import torch
+from timm import create_model
+from timm import resolve_data_config
+from timm.data.transforms_factory import create_transform 
+
+IMAGENET_1k_URL = "https://storage.googleapis.com/bit_models/ilsvrc2012_wordnet_lemmas.txt"
+LABELS = requests.get()
+
+model = create_model('resnet50',pretrained=True)
+transform = create_transform(**resolve_data_config({},model=model))
+
+model.eval()
+
+def predict(img):
+    img = img.convert('RGB')
+    img = transform(img).unsqueeze(0)
+    with torch.no_grad():
+        out=  model(img)
+    probability = torch.nn.functional.softmax(out[0],dim=0)
+
+    values, indices = torch.topk(probability,k=5)
+    return {LABELS[i]: v.items() for i,v in zip(indices,values)}
+
+
+iface = gr.Interface(fn=predict, inputs=gr.inputs.Image(type='pil'), outputs="label").launch()
+iface.launch()

requirements.txt

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+timm
+gradio