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.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
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+*.jpg filter=lfs diff=lfs merge=lfs -text

README.md

@@ -10,4 +10,13 @@ pinned: false
 license: gpl
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Einfache App für Woken-Klassifizierung. Mach ein Foto einer Woke und lasse dir sagen, was für eine Wolke das ist.
+Simple app for cloud classification. Take a picture of a cloud and let it tell you what kind of cloud it is.
+
+Created using fastai and gradio.
+
+First use the imageLoader.py to get you some images (search phrase and folder can be configured in the source).
+Then train the model using train.py
+Afterwards you can run the app.py and point your browser to the shown location.
+
+The model is not very precise as I am no expert. So I'm not really able to sort out wrong classified training data.

app.py

@@ -0,0 +1,27 @@
+from fastai.vision.all import *
+import gradio as gr
+
+path = Path()
+path.ls(file_exts='.pkl')
+learn = load_learner(path/'model.pkl')
+
+labels = {
+        "cirrus": "Cirrus (Federwolke)",
+        "cirrocumulus": "Cirrocumulus (kleine Schäfchenwolke)",
+        "cirrostratus": "Cirrostratus (hohe Schleierwolke)",
+        "altocumulus": "Altocumulus (große Schäfchenwolke)",
+        "altostratus": "Altostratus (mittelhohe Schichtwolke)",
+        "stratocumulus": "Stratocumulus (Haufenschichtwolke)",
+        "stratus": "Stratus (tiefe Schichtwolke)",
+        "cumulus": "Cumulus (Haufenwolke)",
+        "nimbostratus": "Nimbostratus (Regenwolke)",
+        "cumulonimbus": "Cumulonimbus (Gewitterwolke)"
+        }
+
+def predict_cloud_class(img):
+  cloudtype,_,probs = learn.predict(PILImage.create(img))
+  return {labels[learn.dls.vocab[i]]: float(probs[i]) for i in range(len(learn.dls.vocab))}
+
+image = gr.inputs.Image()
+label = gr.outputs.Label(num_top_classes=5)
+gr.Interface(fn=predict_cloud_class, inputs=image, outputs=label,examples=["test_cirrus.jpg","test_cumulus.jpg","test_altocumulus.jpg"]).launch(server_name="0.0.0.0")