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HAMM1.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1f884cd706e2efb3c557119d4d63b26e3766460860f86ae31fa635d0aefb9486
+size 65201629

README.md

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 ---
-title: HAM10000 IMAGE CLASSIFICATION
-emoji: 💻
-colorFrom: blue
+title: HAMMM
+emoji: 🦀
+colorFrom: yellow
 colorTo: blue
 sdk: gradio
-sdk_version: 4.2.0
+sdk_version: 3.3.1
 app_file: app.py
 pinned: false
 license: apache-2.0

app.py

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+!import fastai
+import fastai
+from fastai.vision.all import*
+import gradio as gr
+
+def is_cat(x):returnx[0].isupper()
+
+learn=load_learner('my_export_HAM10000.pkl')
+
+categories=('akiec','bcc','bkl','df','mel','nv','vasc')
+
+def classify_img(img):
+    pred,idx,probs=learn.predict(img)
+    return dict(zip(categories,map(float,probs)))
+    
+image =gr.inputs.Image(shape=(192,192))
+label =gr.outputs.Label()
+example=['mel.jpg','akiec.jpg','vasc.jpg']
+intf=gr.Interface(fn=classify_img,inputs=image,outputs=label,examples=example)
+intf.launch(inline=False)

requirements.txt

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+fastai
+gradio
+pathlib