update .gitattributes so git lfs will track .pkl files and .jpeg

.gitattributes

@@ -33,3 +33,4 @@ 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
+*.jpeg filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,30 @@
+import gradio as gr
+from fastai.vision.all import *
+#import skimage # for interpretation
+
+learn = load_learner('grain_classifier.pkl')
+
+labels = learn.dls.vocab
+def predict(img):
+    pred,pred_idx,probs = learn.predict(img)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+title = "Grain Classifier"
+description = "A grain classifier trained on the xxx online images with fastai. Created as a demo for Gradio and HuggingFace Spaces."
+#article="<p style='text-align: center'><a href='https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial' target='_blank'>Blog post</a></p>"
+examples = ['sample/barley_seed.jpeg', 
+            'sample/corn_seed.jpeg', 
+            'sample/rye_seed.jpeg', 
+            'sample/wheat_seed.jpeg']
+interpretation='default' # what parts of the input are responsible for the output
+enable_queue=True 
+
+gr.Interface(fn=predict,
+             inputs=gr.inputs.Image(shape=(224, 224)),
+             outputs=gr.outputs.Label(num_top_classes=4),
+             title=title,
+             description=description,
+             #article=article,
+             examples=examples,
+             interpretation=interpretation,
+             enable_queue=enable_queue).launch()

grain_classifier.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bfdd9045739bd4e3d6e65e83057bbdd0b87ca4fafae13cdb88595a9ed7bb275e
+size 46979395

requirements.txt

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