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import gradio as gr
import model
from config import app_config
def init():
if model != None:
print("Initializing App...")
app_config.model = model.load_model()
def clear():
return None, 2, None, None, None
def create_interface():
md = """
# Famous Landmark Classifier using CNN
**Choose an image containing any of the `50 possible classes` of world famous landmarks,**
**choose the number of prediction required (k) and hit `Predict`, model will try to identify**
**the landmark in the image.**
**Please note that the model is trained on a small set of only 4,000 images hence it may not**
**be right all the time, but its fun to try out.**
Visit the [project's repo](https://github.com/sssingh/landmark-classification-tagging)
"""
with gr.Blocks(
title=app_config.title, theme=app_config.theme, css=app_config.css
) as app:
with gr.Row():
gr.Markdown(md)
with gr.Accordion(
"Expand to see 50 classes:", open=False, elem_classes="accordion"
):
gr.JSON(app_config.classes, elem_classes="json-box")
with gr.Row():
with gr.Column():
img = gr.Image(type="pil", elem_classes="image-picker")
k = gr.Slider(
label="Number of predictions (k):",
minimum=2,
maximum=5,
value=2,
step=1,
elem_classes="slider",
)
with gr.Row():
submit_btn = gr.Button(
"Predict",
icon="assets/button-icon.png",
elem_classes="submit-button",
)
clear_btn = gr.ClearButton(elem_classes="clear-button")
with gr.Column():
landmarks = gr.JSON(
label="Predicted Landmarks:", elem_classes="json-box"
)
proba = gr.JSON(
label="Predicted Probabilities:", elem_classes="json-box"
)
plot = gr.Plot(container=True, elem_classes="plot")
with gr.Row():
with gr.Accordion(
"Expand for examples:", open=False, elem_classes="accordion"
):
gr.Examples(
examples=[
["assets/examples/gateway-of-india.jpg", 3],
["assets/examples/grand-canyon.jpg", 2],
["assets/examples/opera-house.jpg", 3],
["assets/examples/stone-henge.jpg", 4],
["assets/examples/temple-of-zeus.jpg", 5],
],
inputs=[img, k],
outputs=[landmarks, proba],
elem_id="examples",
)
submit_btn.click(
fn=model.predict, inputs=[img, k], outputs=[landmarks, proba, plot]
)
clear_btn.click(fn=clear, inputs=[], outputs=[img, k, landmarks, proba, plot])
img.clear(fn=clear, inputs=[], outputs=[img, k, landmarks, proba, plot])
return app
if __name__ == "__main__":
init()
app = create_interface()
app.launch()
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