Create app.py

app.py

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+import tensorflow.compat.v2 as tf
+import tensorflow_hub as hub
+import numpy as np
+import pandas as pd
+import cv2
+from skimage import io
+
+m = hub.KerasLayer('https://tfhub.dev/google/aiy/vision/classifier/food_V1/1')
+
+labelmap_url = "https://www.gstatic.com/aihub/tfhub/labelmaps/aiy_food_V1_labelmap.csv"
+input_shape = (224, 224)
+
+def classify_image(inp):
+    inp = inp.reshape((-1, 224, 224, 3))
+    output = m(images)
+    predicted_index = output.numpy().argmax()
+    classes = list(pd.read_csv(labelmap_url)["name"])
+    return {labels[i]: float(prediction[i]) for i in range(1000)}
+    
+image = gr.inputs.Image(shape=(224, 224))
+label = gr.outputs.Label(num_top_classes=3)
+
+gr.Interface(
+    fn=classify_image,
+    inputs=image,
+    outputs=label,
+    examples=[["isachertorte.png"], ["sandwich.jpg"]],
+).launch()