wip

app.py

@@ -1,17 +1,27 @@
-import gradio as gr
+!pip install gradio
+
+__all__ = ['learn', 'classify_image', 'categories', 'image', 'label', 'examples', 'intf']
+
 from fastai.vision.all import *
-import skimage
+import gradio as gr
+import timm
 
 learn = load_learner('model.pkl')
 
 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))}
+
+def classify_image(img):
+    pred,idx,probs = learn.predict(img)
+    return dict(zip(categories, map(float,probs)))
+
+image = gr.Image()
+label = gr.Label()
+
+examples = ['example.jpg']
 
 title = "Melons clasifier"
 interpretation='default'
 enable_queue=True
 
-gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,article=article,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch()