Update app.py

app.py

@@ -1,7 +1,27 @@
 import gradio as gr
+from fastai.vision.all import *
+import skimage
 
-def greet(name):
-    return "Hello " + name + "!!"
+learn = load_learner('final_resnet34_derma_model.pkl')
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+labels = learn.dls.vocab
+
+def predict(img):
+    img = PILImage.create(img)
+    pred, pred_idx, probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+image = gr.inputs.Image(shape=(400, 400))
+label = gr.outputs.Label()
+examples = ['nevus.jpg', 'keratosis.jpg', 'melanoma.jpg']
+
+title = "DermaDoc Skin Lesion Analyzer!"
+description = """This is a simple demo of how deep learning models \
+can be trained for medical applications. \
+The model distinguishes between two benign skin lesions (nevus and keratosis) \
+and a malignant one (melanoma). It has an accuracy of 81 %"""
+interpretation='default'
+enable_queue=True
+
+iface = gr.Interface(fn=predict, inputs=image, outputs=label,title=title, description=description, article=article, examples=examples, interpretation=interpretation, enable_queue=enable_queue)
 iface.launch()