added

app-Copy1.py

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+
+import streamlit as st
+from PIL import Image
+import urllib.request
+import torch
+from torch import nn
+import numpy as np
+from VT5 import VT5
+from transformers import (
+    AutoModelForSeq2SeqLM,
+    AutoTokenizer,
+    Trainer,
+    TrainingArguments,
+    T5Tokenizer, 
+    T5ForConditionalGeneration,
+    CLIPVisionModelWithProjection,
+    AutoProcessor
+)
+
+  
+clip = CLIPVisionModelWithProjection.from_pretrained("openai/clip-vit-base-patch32")
+processor = AutoProcessor.from_pretrained("openai/clip-vit-base-patch32")
+
+default_img = Image.open("gfg.png")
+default_img = processor(images=default_img,return_tensors='pt').pixel_values
+
+
+tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-small")
+t5 = T5ForConditionalGeneration.from_pretrained("google/flan-t5-small")
+
+vt5 = VT5(t5,tokenizer,clip)
+vt5.load_state_dict(torch.load('weights.bin',map_location=torch.device('cpu')))
+
+# Assuming you have this function that generates captions
+def generate_caption(image):
+    # Your model code here
+    caption = "This is a placeholder caption"
+    print(image)
+    caption = vt5.generate_caption(image)
+    return caption
+
+st.title("Image Captioning App")
+#st.image(image.numpy().reshape(224,224,3), caption='Uploaded Image.', clamp=True,use_column_width=True)
+uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "png","jpeg"])
+
+if uploaded_file is not None:
+    image = Image.open(uploaded_file)
+    st.image(image, caption='Uploaded Image.', clamp=True,use_column_width=True)
+   
+    st.write("")
+    st.write("Generating caption...")
+    caption = generate_caption(image)
+    st.write("Caption: ", caption)