Upload folder using huggingface_hub

app.py

@@ -1,7 +1,20 @@
 import gradio as gr
+from fastai.vision.all import *
+#from huggingface_hub import push_to_hub_fastai
+from huggingface_hub import HfApi
+api = HfApi()
+repo_id = "JaxHax/ArduinoClassifier"
+api.upload_folder(repo_id=repo_id, repo_type="space", folder_path="./")
+learn = load_learner('model.pkl')
+#push_to_hub_fastai(learner=learn, repo_id=repo_id)
+catagories = ('Mega', 'Nano', 'Uno')
+def classify_image(img):
+	pred,idx,probs = learn.predict(img)
+	return dict(zip(catagories, map(float,probs)))
 
-def greet(name):
-    return "Hello " + name + "!!"
+image = gr.inputs.Image(shape=(192,192))
+label = gr.outputs.Label()
+examples = ['uno.jpg', 'nano.jpg', 'mega.jpg']
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch(inline=False)

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e96d85144350b085be4773382e96bec8050ab6d1784c66051b9156167636f2a2
+size 46968253