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import gradio as gr
from PIL import Image
import hopsworks
# IDE Help
from hopsworks.core.dataset_api import DatasetApi
# Images
hopsworks_images_location = "Resources/images"
hopsworks_images = {
"latest_iris":
{
"name": "latest_iris.png",
"local_path": ""
},
"actual_iris":
{
"name": "actual_iris.png",
"local_path": ""
},
"df_recent":
{
"name": "df_recent.png",
"local_path": ""
},
"confusion_matrix":
{
"name": "confusion_matrix.png",
"local_path": ""
}
}
print("Logging in to Hopsworks...")
project = hopsworks.login()
print("Getting feature store...")
fs = project.get_feature_store()
print("Get database handler from Hopsworks...")
dataset_api: DatasetApi = project.get_dataset_api()
for image in hopsworks_images:
print(f"Downloading {hopsworks_images[image]['name']} from Hopsworks...")
hopsworks_images[image]['local_path'] = dataset_api.download(f"{hopsworks_images_location}/{hopsworks_images[image]['name']}")
print(f"Saved in: {hopsworks_images[image]['local_path']}")
print("Configuring gradio...")
with gr.Blocks() as demo:
with gr.Row():
with gr.Column():
label1 = gr.Label("Today's Predicted Image")
image1 = gr.Image(hopsworks_images['latest_iris']['local_path'],
elem_id="predicted-img", type="pil")
with gr.Column():
label2 = gr.Label("Today's Actual Image")
image2 = gr.Image(hopsworks_images['actual_iris']['local_path'],
elem_id="actual-img", type="pil")
with gr.Row():
with gr.Column():
label3 = gr.Label("Recent Prediction History")
image3 = gr.Image(hopsworks_images['df_recent']['local_path'],
elem_id="recent-predictions", type="pil")
with gr.Column():
label4 = gr.Label("Confusion Matrix with Historical Prediction Performance")
image4 = gr.Image(hopsworks_images['confusion_matrix']['local_path'],
elem_id="confusion-matrix", type="pil")
print("Launching gradio...")
demo.launch(debug=True)
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