app commit

app.py

@@ -1,7 +1,28 @@
 import gradio as gr
+from fastai.vision.all import *
+import skimage
+import timm
+learn = load_learner('/content/drive/MyDrive/Rice Category Prediction/export.pkl')
 
-def greet(name):
-    return "Hey" + name + "!!"
+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))}
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+title = "Rice Category 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 = ['/content/drive/MyDrive/Rice Category Prediction/Arborio.jpg',
+              '/content/drive/MyDrive/Rice Category Prediction/Basmati.jpg',
+              '/content/drive/MyDrive/Rice Category Prediction/Jasmine.jpg',
+              '/content/drive/MyDrive/Rice Category Prediction/Ispala.jpg',
+              '/content/drive/MyDrive/Rice Category Prediction/Karacadag.jpg'
+
+          ]
+interpretation='default'
+enable_queue=True
+
+demo = gr.Interface(fn=predict, inputs="image", outputs="label",examples= examples)
+if __name__ == "__main__":
+    demo.launch()

export.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0627f01583c64be5631e3d83746f89c83b3cae9d282b280180b5846a198ea503
+size 103743675