Update app.py

app.py

@@ -1,11 +1,12 @@
 import gradio as gr
-from transformers import AutoProcessor,  AutoModelForCausalLM, pipeline
+from transformers import AutoProcessor, AutoModelForCausalLM
 import torch
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 checkpoint1 = "ayoubkirouane/git-base-One-Piece"
 processor = AutoProcessor.from_pretrained(checkpoint1)
 model1 = AutoModelForCausalLM.from_pretrained(checkpoint1)
+
 def img2cap(image):
     input1 = processor(images=image, return_tensors="pt").to(device)
     pixel_values1 = input1.pixel_values
@@ -13,15 +14,14 @@ def img2cap(image):
     generated_caption1 = processor.batch_decode(generated_id1, skip_special_tokens=True)[0]
     return generated_caption1
 
-
-examples = ["1.png" ,"2.png" , "3.png" ]
+examples = ["1.png", "2.png", "3.png"]
 
 gr.Interface(
-    img2cap,
-    inputs = gr.inputs.Image(type="pil", label="Original Image"),
-    outputs= gr.outputs.Textbox(label="The generated caption:"),
-    title = "Image Captioning using git-base-One-Piece Model",
-    description = "git-base-One-Piece is used to generate Image Caption for the uploaded image.",
+    fn=img2cap,
+    inputs=gr.Image(type="pil", label="Original Image"),
+    outputs=gr.Textbox(label="The generated caption:"),
+    title="Image Captioning using git-base-One-Piece Model",
+    description="git-base-One-Piece is used to generate Image Caption for the uploaded image.",
     examples=examples,
     theme="huggingface",
-).launch(debug=True)
+).launch(debug=True)