asfassdegf

app.py

@@ -1,3 +1,4 @@
+from typing import Any
 import gradio as gr
 import hopsworks
 from PIL import Image
@@ -12,7 +13,7 @@ dataset_api.download("Resources/images/actual_wine.png", overwrite=True)
 dataset_api.download("Resources/images/df_wine_recent.png", overwrite=True)
 dataset_api.download("Resources/images/wine_confusion_matrix.png", overwrite=True)
 
-def load_images():
+""" def load_images():
     project = hopsworks.login()
     dataset_api = project.get_dataset_api()
 
@@ -21,7 +22,20 @@ def load_images():
     dataset_api.download("Resources/images/df_wine_recent.png", overwrite=True)
     dataset_api.download("Resources/images/wine_confusion_matrix.png", overwrite=True)
 
-    return Image.open("wine_confusion_matrix.png")
+    return Image.open("wine_confusion_matrix.png") """
+
+
+class ImageLoad:
+    def __init__(self, path:str) -> None:
+        self.path = path
+        self.image_name = path[path.rfind('/') + 1:]
+        print(self.image_name)
+
+    def __call__(self):
+        project = hopsworks.login()
+        dataset_api = project.get_dataset_api()
+        dataset_api.download(self.path, overwrite=True)
+        return Image.open(self.image_name)
 
 
 
@@ -29,21 +43,21 @@ with gr.Blocks() as demo:
     with gr.Row():
       with gr.Column():
           gr.Label("Today's Predicted Image")
-          
-          input_img = gr.Image("latest_wine.png", elem_id="predicted-img")
+          input_img = gr.Image(value=ImageLoad("Resources/images/latest_wine.png"), elem_id="predicted-img")
       with gr.Column():          
           gr.Label("Today's Actual Image")
-          input_img = gr.Image("actual_wine.png", elem_id="actual-img")        
+          input_img = gr.Image(value=ImageLoad("Resources/images/actual_wine.png"), elem_id="actual-img")        
     with gr.Row():
       with gr.Column():
           gr.Label("Recent Prediction History")
-          input_img = gr.Image("df_wine_recent.png", elem_id="recent-predictions")
+          input_img = gr.Image(value=ImageLoad("Resources/images/df_wine_recent.png"), elem_id="recent-predictions")
       with gr.Column():          
           gr.Label("Confusion Maxtrix with Historical Prediction Performance")
           #input_img = gr.Image("wine_confusion_matrix.png", elem_id="confusion-matrix")     
-          image = gr.Image(show_label=False)
+          """ image = gr.Image(show_label=False)
           demo.load(fn=load_images, inputs=None, outputs=image,
-                show_progress=False)   
+                show_progress=False)  """  
+          input_img = gr.Image(value=ImageLoad("Resources/images/wine_confusion_matrix.png"), elem_id="recent-predictions")
     #demo.load(load_images)
 
 #load_images()