Create app.py

app.py

@@ -0,0 +1,29 @@
+import onnxruntime 
+import gradio as gr
+import os
+from PIL import Image
+
+
+model_path  = 'multi_target_resnet50.pkl'
+
+model = load_learner(model_path)
+
+def result(path):  
+  
+  pred,_,probability = model.predict(path)
+
+  return pred
+
+path = 'test images/'
+
+image_path = []
+
+for i in os.listdir(path):
+  image_path.append(path+i) 
+
+
+image = gr.inputs.Image(shape =(300,300))
+label = gr.outputs.Label()
+
+iface = gr.Interface(fn=result, inputs=image, outputs=label, examples = image_path)
+iface.launch(inline = False)