commit

.python-version

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+3.7.6

README.md

@@ -7,6 +7,7 @@ sdk: gradio
 sdk_version: 3.1.4
 app_file: app.py
 pinned: false
+python_version: 3.7.6
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import tensorflow as tf
+import numpy as np
+from PIL import Image
+import tensorflow.keras as keras
+import keras.applications.xception as xception
+from tensorflow.keras.models import load_model
+ 
+# load model
+model = load_model('model12.h5')
+
+classnames = ['battery','biological','brown-glass','cardboard','clothes','green-glass','metal','paper','plastic','shoes','trash','white-glass']
+
+
+
+def predict_image(img):
+  img_4d=img.reshape(-1,320, 320,3)
+  prediction=model.predict(img_4d)[0]
+  return {classnames[i]: float(prediction[i]) for i in range(12)}
+
+image = gr.inputs.Image(shape=(320, 320))
+label = gr.outputs.Label(num_top_classes=3)
+enable_queue=True
+examples = ['battery.jpg','cardboard.jpeg','clothes.jpeg','glass.jpg','metal.jpg','plastic.jpg','shoes.jpg']
+article="<p style='text-align: center'>Made by Aditya Narendra with 🖤</p>"
+
+gr.Interface(fn=predict_image, inputs=image,  title="Garbage Classifier",
+    description="This is a Garbage Classification Model Trained using Xception Net.Deployed to Hugging Faces using Gradio.",outputs=label,article=article,enable_queue=enable_queue,examples=examples,interpretation='default').launch(share="True")

model804.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:adba5e3a50ae004a826f1ff3df5c5841b7ec59e781cff0fe7a9ee158d8724fb2
+size 83963016