app

app.py

@@ -6,8 +6,8 @@ import numpy as np
 
 model = from_pretrained_keras("keras-io/timeseries_transformer_classification")
 
-def detect_issue(df):
-  #df = pd.read_csv('sample.csv',header=None)
+def detect_issue(file):
+  df = pd.read_csv(file,header=None)
   pred = model.predict(df)[0]
   problem = 'No problem'
   if(np.argmax(pred)==1):
@@ -15,7 +15,7 @@ def detect_issue(df):
   return problem, pred[1]
   
 
-iface = gr.Interface(detect_issue,"dataframe",
+iface = gr.Interface(detect_issue,gr.inputs.File(label="csv file"),
 	outputs=[
 	        gr.outputs.Textbox(label="Engine issue"),
        		gr.outputs.Textbox(label="Engine issue score")], examples=["sample.csv"]