daniel-rdt's picture
update in app interface
c05c5fe
import gradio as gr
import imageio.v3 as iio
import hopsworks
project = hopsworks.login(api_key_value='U6PiDFwDVDQHP26X.XhXDZQ9QKiNwafhLh11PUntcyYW5Zp8aoXhoj1IJTGHDBu8owQJUKbFClHaehyMU')
fs = project.get_feature_store()
dataset_api = project.get_dataset_api()
dataset_api.download("Resources/images/latest_bitcoin_fluctuation_prediction.png", overwrite=True)
dataset_api.download("Resources/images/latest_bitcoin_fluctuation_actual.png", overwrite=True)
dataset_api.download("Resources/images/df_recent.png", overwrite=True)
dataset_api.download("Resources/images/confusion_matrix.png", overwrite=True)
def update():
dataset_api.download("Resources/images/latest_bitcoin_fluctuation_prediction.png", overwrite=True)
dataset_api.download("Resources/images/latest_bitcoin_fluctuation_actual.png", overwrite=True)
dataset_api.download("Resources/images/df_recent.png", overwrite=True)
dataset_api.download("Resources/images/confusion_matrix.png", overwrite=True)
def update_fluctuation_prediction_img():
im_pred = iio.imread('latest_bitcoin_fluctuation_prediction.png')
return im_pred
def update_actual_fluctuation_img():
im_act = iio.imread('latest_bitcoin_fluctuation_actual.png')
return im_act
def update_df_recent_img():
im_hist = iio.imread('df_recent.png')
return im_hist
def update_confusion_matrix_img():
im_matr = iio.imread('confusion_matrix.png')
return im_matr
with gr.Blocks() as demo:
with gr.Row():
load=gr.Button("Load Images")
load.click(fn=update)
with gr.Row():
refresh=gr.Button("Refresh (wait 10 seconds after loading images before refreshing)")
with gr.Row():
with gr.Column():
gr.Label("Today's Predicted Image")
input_img_pred = gr.Image("latest_bitcoin_fluctuation_prediction.png", elem_id="predicted-img")
refresh.click(update_fluctuation_prediction_img,outputs=input_img_pred)
with gr.Column():
gr.Label("Today's Actual Image")
input_img_act = gr.Image("latest_bitcoin_fluctuation_actual.png", elem_id="actual-img")
refresh.click(update_actual_fluctuation_img,outputs=input_img_act)
with gr.Row():
with gr.Column():
gr.Label("Recent Prediction History")
input_img_hist = gr.Image("df_recent.png", elem_id="recent-predictions")
refresh.click(update_df_recent_img,outputs=input_img_hist)
with gr.Column():
gr.Label("Confusion Maxtrix with Historical Prediction Performance")
input_img_matr = gr.Image("confusion_matrix.png", elem_id="confusion-matrix")
refresh.click(update_confusion_matrix_img,outputs=input_img_matr)
demo.launch()