pokemon model

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 from fastai.vision.all import *
 import skimage
 
-def is_cat(x): return x[0].isupper()
+def is_pokemon(x): return x.parent_label
  
 learn = load_learner('export.pkl')
 
@@ -12,11 +12,10 @@ def predict(img):
     pred,pred_idx,probs = learn.predict(img)
     return {labels[i]: float(probs[i]) for i in range(len(labels))}
 
-title = "Pet Breed Classifier"
-description = "A pet breed classifier trained on the Oxford Pets dataset 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 = ['siamese.jpg']
+title = "Pokemon Classifier"
+description = "is it a pokemon"
+examples = ['vulpix.jpg']
 interpretation='default'
 enable_queue=True
 
-gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,article=article,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()
+gr.Interface(fn=predict,inputs=gr.inputs.Image(shape=(512, 512)),outputs=gr.outputs.Label(num_top_classes=3),title=title,description=description,examples=examples,interpretation=interpretation,enable_queue=enable_queue).launch()

model.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e7c2ab34378e55e73df18ba52048a9e45369aa2896dee9397c4a35f9d7ab6b4f
-size 47061355
+oid sha256:599070bcfabbcd0528cf216989def22c0a99862956fe5559af496d2ff7555cc4
+size 46966831