added code + images

.gitattributes

@@ -26,3 +26,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zstandard filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 rn50_256px_18genre_10epoch_err313.pkl filter=lfs diff=lfs merge=lfs -text
+Image06.jpg filter=lfs diff=lfs merge=lfs -text
+Image08.jpg filter=lfs diff=lfs merge=lfs -text
+Image04.jpg filter=lfs diff=lfs merge=lfs -text
+Image09.jpg filter=lfs diff=lfs merge=lfs -text
+Image02.jpg filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,24 @@
+import gradio as gr
+from fastai.vision.all import *
+import skimage
+
+learn = load_learner('rn50_256px_18genre_10epoch_err313.pkl')
+
+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))}
+
+examples = [f"Image{n:02d}.jpg" for n in range(10)]
+interpretation='default'
+title = "Art Movement Classifier - WikiArt"
+description = "What Art Movement Matches the Image Best?"
+
+gr.Interface(fn=predict,
+             inputs=gr.inputs.Image(shape=((512,512))),
+             outputs=gr.outputs.Label(num_top_classes=5),
+             title = title,
+             examples =  examples,
+             interpretation = interpretation,
+             description = description).launch(share=True, enable_queue=True)

requirements.txt

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