deploy

app.py

@@ -1,7 +1,19 @@
 import gradio as gr
+from fastai.vision.all import *
+import skimage
 
-def greet(name):
-    return "Hello " + name + "!!"
+learn = load_learner('model.pkl')
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+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))}
+
+title = "Pet Classifier"
+description = "A pet classifier created as a demo for Gradio and HuggingFace Spaces."
+examples = ['dunno.jpg', 'dog.jpeg']
+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()

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f6576016c30a90a0a11ce730e49be18059c7a18fe9c4c632af5690ea58f4989e
+size 103032485

requirements.txt

@@ -0,0 +1,2 @@
+fastai
+scikit-image