Create app.py

app.py

@@ -0,0 +1,53 @@
+import streamlit as st
+import torch
+from PIL import Image
+import requests
+from transformers import BlipForConditionalGeneration, BlipForQuestionAnswering, BlipProcessor
+
+
+## Loading BLIP image caption model
+processor = BlipProcessor.from_pretrained("adit94/blip_humour")
+model = BlipForConditionalGeneration.from_pretrained("adit94/blip_humour")
+
+device = "cuda" if torch.cuda.is_available() else "cpu"
+
+
+def blip_generate(prompt, img):
+    #raw_image = Image.open(requests.get(img_url, stream=True).raw).convert('RGB')
+    img = img.convert('RGB')
+    inputs = processor(img, return_tensors="pt").to(device)
+    
+    outputs = model.generate(
+        **inputs,
+        do_sample=False,
+        num_beams=5,
+        max_length=256,
+        min_length=1,
+        top_p=0.9,
+        repetition_penalty=1.5,
+        length_penalty=1.0,
+        temperature=1,
+    )
+
+    generated_text = processor.batch_decode(outputs, skip_special_tokens=True)[0].strip()
+
+    return generated_text
+
+st.set_page_config(
+    page_title="Humour Detection",
+    initial_sidebar_state = 'auto'
+)
+
+file = st.file_uploader("", type=["jpg", "png"])
+
+if file is None:
+    st.text("Please upload an image file")
+else:
+    image = Image.open(file)
+    st.image(image)
+
+    caption = blip_generate()
+
+    st.text('Predicted output')
+    st.text(caption)
+