Add initial application with sample images

app.py

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+import numpy as np
+import tensorflow as tf
+import gradio as gr
+from huggingface_hub import hf_hub_download
+from PIL import Image
+
+model_path = hf_hub_download(
+    repo_id="tancnle/smart-recycling",
+    filename="model_baseline.h5",
+    use_auth_token="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",
+)
+
+dim = (299, 299)
+
+
+def read_image(image):
+    image = Image.open(image)
+    image_np = np.array(image)
+    image_np = tf.expand_dims(tf.cast(np.resize(image, dim), tf.float32) / 255.0, -1)
+    image_np = tf.image.grayscale_to_rgb(image_np)
+    return image
+
+
+def infer(model, image_tensor):
+    predictions = model.predict(tf.expand_dims(image_tensor, axis=0))
+    return predictions
+
+
+def classify(input_image):
+    image_tensor = read_image(input_image)
+    predictions = infer(image_tensor)
+    return predictions
+
+
+examples = [["cardboard116.jpg"]]
+title = "Classify Trash"
+description = "Upload an image or select from examples to classify trash."
+article = "<div style='text-align: center;'>Space by Tan Le</div>"
+
+demo = gr.Interface(
+    classify,
+    inputs="image",
+    outputs="label",
+    examples=examples,
+    title=title,
+    description=description,
+    article=article,
+)
+demo.launch()

requirements.txt

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+numpy
+pillow
+tensorflow