data

app.py

@@ -58,7 +58,7 @@ species = np.load("data/species_70b.npy", allow_pickle=True)
 clas = np.load("data/class_70b.npy", allow_pickle=True)
 order = np.load("data/order_70b.npy", allow_pickle=True)
 #genus = np.load("genus_70b.npy")
-family = np.load("family_70b.npy")
+family = np.load("data/family_70b.npy")
 
 species_list = list(species[()].keys())
 class_list = list(clas[()].keys())
@@ -97,7 +97,7 @@ def text_fn(taxon, name):
     rgba_img = cmap(preds)
     rgb_img = np.delete(rgba_img, 3, 2)
     #return gr.Image(preds, label="Predicted Heatmap", visible=True)
-    return taxon + ": " + name + ": " + str(np.mean(preds)), rgb_img
+    return rgb_img
 
 def pred_fn(taxon, name):
     if taxon=="Class":
@@ -125,17 +125,17 @@ with gr.Blocks() as demo:
     with gr.Row():
         inp = gr.Dropdown(label="Taxonomic Hierarchy", choices=["Class", "Order", "Family", "Genus", "Species"])
         out = gr.Dropdown(label="Name", interactive=True)
-        text = gr.Textbox(label="Text", visible=True, interactive=True)
         inp.change(update_fn, inp, out)
     
     with gr.Row():
-        check_button = gr.Button("Check")
-        submit_button = gr.Button("Run Model")
+        check_button = gr.Button("Run Model")
+    
+    with gr.Row():
+        slider = gr.Slider(minimum=0, maximum=1, step=0.01, default=0.5, label="Confidence Threshold")
     
     with gr.Row():
         pred = gr.Image(label="Predicted Heatmap", visible=True)
     
-    check_button.click(text_fn, inputs=[inp, out], outputs=[text, pred])
-    #submit_button.click(pred_fn, inputs=[inp, out], outputs=[pred])
+    check_button.click(text_fn, inputs=[inp, out], outputs=[pred])
     
 demo.launch()