CPU version of the code

app.py

@@ -1,13 +1,11 @@
-import torch
 import requests
 from PIL import Image
 from transformers import BlipProcessor, BlipForConditionalGeneration
 import gradio as gr
-device="cpu"
+
 processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
-model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base", torch_dtype=torch.float16).to(device)
+model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
 
-# Function to process the image and generate captions
 def generate_caption(image, caption_type, text):
     raw_image = Image.fromarray(image.astype('uint8'), 'RGB')
     
@@ -18,28 +16,21 @@ def generate_caption(image, caption_type, text):
     
     return caption
 
-# Conditional image captioning
 def conditional_image_captioning(raw_image, text):
-    inputs = processor(raw_image, text, return_tensors="pt").to(device, torch.float16)
+    inputs = processor(raw_image, text, return_tensors="pt")
     out = model.generate(**inputs)
     caption = processor.decode(out[0], skip_special_tokens=True)
     return caption
 
-# Unconditional image captioning
 def unconditional_image_captioning(raw_image):
-    inputs = processor(raw_image, return_tensors="pt").to(device, torch.float16)
+    inputs = processor(raw_image, return_tensors="pt")
     out = model.generate(**inputs)
     caption = processor.decode(out[0], skip_special_tokens=True)
     return caption
 
-# Interface setup
-input_image = gr.inputs.Image()
+input_image = gr.inputs.Image(label="Upload an Image")
 input_text = gr.inputs.Textbox(label="Enter Text (for Conditional Captioning)")
-
-choices = ["Conditional", "Unconditional"]
-radio_button = gr.inputs.Radio(choices, label="Captioning Type")
-
+radio_button = gr.inputs.Radio(choices=["Conditional", "Unconditional"], label="Captioning Type")
 output_text = gr.outputs.Textbox(label="Caption")
 
-# Create the interface
-gr.Interface(fn=generate_caption, inputs=[input_image, radio_button, input_text], outputs=output_text, title="Image Captioning",debug=True).launch()
+gr.Interface(fn=generate_caption, inputs=[input_image, radio_button, input_text], outputs=output_text, title="Image Captioning").launch()