Initial commit

app.py

@@ -0,0 +1,45 @@
+import streamlit as st
+from transformers import VisionEncoderDecoderModel, AutoFeatureExtractor, AutoTokenizer
+import requests
+from PIL import Image
+import torch
+
+
+CHECKPOINT = "g8a9/vit-geppetto-captioning"
+model = VisionEncoderDecoderModel.from_pretrained(CHECKPOINT)
+feature_extractor = AutoFeatureExtractor.from_pretrained(CHECKPOINT)
+tokenizer = AutoTokenizer.from_pretrained(CHECKPOINT)
+
+model.eval()
+
+
+def generate_caption(url):
+    image = Image.open(requests.get(url, stream=True).raw).convert("RGB")
+    inputs = feature_extractor(image, return_tensors="pt")
+    generated_ids = model.generate(
+        inputs["pixel_values"],
+        max_length=20,
+        num_beams=5,
+        early_stopping=True,
+        no_repeat_ngram_size=2,
+        num_return_sequences=3,
+    )
+    captions = tokenizer.batch_decode(
+        generated_ids,
+        skip_special_tokens=True,
+    )
+    return captions[0]
+
+
+st.title("Captioning demo")
+
+url = st.text_input(
+    "Insert your URL", "https://iheartcats.com/wp-content/uploads/2015/08/c84.jpg"
+)
+
+st.image(url)
+
+if st.button("Run captioning"):
+    with st.spinner("Processing image..."):
+        caption = generate_caption(url)
+        st.text(caption)