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added demo files
Browse files- app.py +94 -0
- requirements.txt +2 -0
app.py
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import tensorflow as tf
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from keras.losses import SparseCategoricalCrossentropy
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from keras.metrics import SparseCategoricalAccuracy
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from PIL import Image
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import numpy as np
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from huggingface_hub import from_pretrained_keras
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import gradio as gr
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# prepare model
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model = from_pretrained_keras("viola77data/recycling")
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optimizer = tf.keras.optimizers.Adam(learning_rate=3e-5)
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cls_loss = SparseCategoricalCrossentropy()
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cls_acc = SparseCategoricalAccuracy()
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model.compile(optimizer=optimizer, loss=cls_loss, metrics=[cls_acc])
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# prepare the categories
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categories = ['aluminium', 'batteries', 'cardboad',
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'disposable plates', 'glass', 'hard plastic',
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'paper', 'paper towel', 'polystyrene',
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'soft plastics', 'takeaway cups']
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dict_recycle = {
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'aluminium': 'recycle',
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'batteries': 'recycle',
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'cardboad': 'recycle',
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'disposable plates': 'dont recycle',
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'glass': 'recycle',
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'hard plastic': 'recycle',
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'paper': 'recycle',
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'paper towel': 'recycle',
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'polystyrene': ' dont recycle',
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'soft plastics': 'dont recycle',
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'takeaway cups': 'dont recycle'
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}
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# prediction functions
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def preprocess_image(im):
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""" Pass in a numpy image an it returns a
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TF Image"""
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im = tf.cast(im, tf.float32) / 255.0
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if len(im.shape) < 3:
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im = tf.expand_dims(im, axis=-1) # add the channel dimension
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im = tf.image.grayscale_to_rgb(im)
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im = tf.image.resize(im, (224, 224))
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im = tf.expand_dims(im, axis=0)
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return im
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def classify_image(input):
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input_processed = preprocess_image(input)
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preds = model.predict(input_processed)[0]
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cls_preds = dict(zip(categories, map(float, preds)))
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predicted_class = categories[np.argmax(preds)]
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recycle_preds = dict_recycle[predicted_class]
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return cls_preds, recycle_preds
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# Defining the Gradio Interface
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# This is how the Demo will look like.
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title = "Should I Recycle This?"
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description = """
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This app was created to help people recycle the right type of waste.
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You can use it at the comfort of your own home. Just take a picture of the waste material you want to know if
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its recyclible and upload it to this app and using Artificial Intelligence it will determine if you should
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throw the waste in the recycling bin or the normal bin.
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Enjoy!
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Made by Viola, you can reach out to me here:
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"""
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image = gr.Image(shape=(224,224))
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label = gr.Label(num_top_classes=3, label='Prediction Material')
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recycle = gr.Textbox(label='Should you recycle?')
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outputs = [label, recycle]
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intf = gr.Interface(fn=classify_image, inputs=image, outputs=outputs, title = title, description = description,
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cache_examples=False)
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intf.launch(enable_queue=True)
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requirements.txt
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tensorflow==2.9.1
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keras=2.9.0
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