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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 gradio as gr | |
from hub.tensorflow_hub.hf_utils import pull_from_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 != ""] | |
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 prediction | |
iface = gr.Interface(fn=predict_fn, | |
inputs=gr.Image(shape=(224, 224)), | |
outputs=gr.Label(num_top_classes=5)) | |
iface.launch() |