trying to add bars in output

app.py

@@ -6,7 +6,6 @@ from tensorflow.keras.models import load_model
 
 # Load the pre-trained model
 model = load_model('my_model.h5')
-CATEGORIES = ("NSFW", "SFW")
 def classify_image(img):
  # Preprocess the input image
  img = image.img_to_array(img)
@@ -14,15 +13,11 @@ def classify_image(img):
  img /= 255.0
  
  # Use the model to make a prediction
- prediction = model.predict(img)
- print(prediction)
+ prediction = model.predict(img)[0]
+ #print(prediction)
  # Map the predicted class to a label
- if prediction[0][0] >= 0.5:
- label = "SFW"
- else:
- label = "NSFW"
- 
- return label
+ dic = {'SFW': np.round(prediction[1],2), 'NSFW': np.round(prediction[0],2)}
+ return dic#{'SFW': prediction[0][1], 'NSFW': prediction[0][0]}
 
 def classify_url(url):
  # Load the image from the URL
@@ -35,10 +30,10 @@ def classify_url(url):
 #inputs = gr.inputs.Image(shape=(224, 224, 3))
 
 # Define the GRADIO output interface
-#outputs = gr.outputs.Textbox(lines=1, default="SFW")
+
 
 # Define the GRADIO app
-app = gr.Interface(classify_image, gr.Image(shape=(224, 224)), outputs=gr.Label(label="Type of Image"), allow_flagging="never", title="NSFW/SFW Classifier")
+app = gr.Interface(classify_image, gr.Image(shape=(224, 224)), outputs="label", allow_flagging="never", title="NSFW/SFW Classifier")
 
 # Start the GRADIO app
 app.launch()

my_model.h5

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:72f973a8a272937a04f5ea32eb48539a61338694d310a7abe805e89de29f4ff4
-size 94864144
+oid sha256:ff20523d0b47e5980145186785b93d4ebb2fa858759ab9c7bb452476955b1663
+size 189463232