resolving errors

app.py

@@ -2,15 +2,13 @@ import gradio as gr
 from fastbook import *
 from fastai.vision.widgets import *
 import timm
-import gradio as gr
-categories = ('accident' , 'non-accident')
+categories = ['accident' , 'non-accident']
 learn = load_learner('model.pkl')
 def classify(img):
-  categories,index,probs = learn.predict(img)
-  return dict(zip(categories , map(float,probs)))
+  category,index,probs = learn.predict(img)
+  return (dict(zip(categories , map(float,probs))))
 img = gr.inputs.Image(shape=(224))
 label = gr.outputs.Label()
 example = ['accident.jpg' , 'non-accident.jpg']
-
 iface = gr.Interface(fn=classify, inputs="image", outputs="label" , examples= example)
 iface.launch()

flagged/log.csv

@@ -0,0 +1,2 @@
+img,output,flag,username,timestamp
+/home/manoj/accident_model/accident_detection/flagged/img/tmpoxic_h49.jpg,/home/manoj/accident_model/accident_detection/flagged/output/tmp36k9kjmf.json,,,2023-05-03 07:37:51.154637

flagged/output/tmp36k9kjmf.json

@@ -0,0 +1 @@
+{"label": "A", "confidences": [{"label": "accident", "confidence": 0.9861869812011719}, {"label": "non-accident", "confidence": 0.013813060708343983}]}