v0.1

.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpg filter=lfs diff=lfs merge=lfs -text

app.py

@@ -1,7 +1,30 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: app.ipynb.
+
+# %% auto 0
+__all__ = ['learn', 'categories', 'im', 'image', 'label', 'examples', 'intf', 'classify_image']
+
+# %% app.ipynb 1
+from fastai.vision.all import *
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+# %% app.ipynb 2
+learn = load_learner('export.pkl')
+
+# %% app.ipynb 7
+categories = ('dreckig', 'sauber')
+im = PILImage.create('packstation_sauber.jpg')
+im.thumbnail((192,192))
+im
+
+learn.predict(im)
+def classify_image(img):
+    prod,idx,probs = learn.predict(img)
+    return dict(zip(categories, map(float,probs)))
+
+# %% app.ipynb 9
+image = gr.inputs.Image(shape=(192,192))
+label = gr.outputs.Label()
+examples = ['packstation_sauber.jpg', 'packstation_dreckig.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)