Adding initial template

app.py

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+# Workaround to install the lib without "setup.py"
+import sys
+from git import Repo
+Repo.clone_from("https://github.com/dimitreOliveira/hub.git", "./hub")
+sys.path.append("/hub")
+
+import requests
+# Download human-readable labels for ImageNet.
+response = requests.get("https://storage.googleapis.com/download.tensorflow.org/data/ImageNetLabels.txt")
+labels = [x for x in response.text.split("\n") if x != ""]
+
+
+import gradio as gr
+import tensorflow as tf
+from hub.tensorflow_hub.hf_utils import pull_from_hub
+
+model = pull_from_hub(repo_id="Dimitre/mobilenet_v3_small")
+
+def preprocess(image):
+    print(image)
+    print("***********")
+    image = image.reshape((-1, 224, 224, 3))
+    print(image)
+    print("***********")
+    print(image / 255.)
+    return image / 255.
+
+def postprocess(prediction):
+    return {labels[i]: prediction[i] for i in range(len(labels))}
+
+def predict_fn(image):
+    image = preprocess(image)
+    prediction = model([image])
+    scores = postprocess(prediction)
+    return scores
+
+iface = gr.Interface(fn=predict_fn, 
+                     inputs=gr.Image(shape=(224, 224)), 
+                     outputs=gr.Label(num_top_classes=5))
+iface.launch()

requirements.txt

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+GitPython
+tensorflow