| import io |
| import os |
| import streamlit as st |
| import requests |
| from PIL import Image |
| from model import get_caption_model, generate_caption |
| import gradio as gr |
|
|
|
|
| @st.cache(allow_output_mutation=True) |
| def get_model(): |
| return get_caption_model() |
|
|
| caption_model = get_model() |
|
|
|
|
| def predict(): |
| captions = [] |
| pred_caption = generate_caption('tmp.jpg', caption_model) |
|
|
| |
| captions.append(pred_caption) |
|
|
| for _ in range(4): |
| pred_caption = generate_caption('tmp.jpg', caption_model, add_noise=True) |
| if pred_caption not in captions: |
| captions.append(pred_caption) |
| |
| |
| return captions; |
| def launch(inputs): |
| img = Image.open(requests.get(inputs, stream=True).raw) |
| img = img.convert('RGB') |
| st.image(img) |
| img.save('tmp.jpg') |
| o=predict() |
| str1="" |
| for ele in o: |
| str1 += "\n"+ele |
| os.remove('tmp.jpg') |
| return str1 |
| iface = gr.Interface(launch, inputs="text", outputs="text") |
| iface.launch(debug=True) |
|
|
| '''st.title('Image Captioner') |
| img_url = st.text_input(label='Enter Image URL') |
| |
| if (img_url != "") and (img_url != None): |
| img = Image.open(requests.get(img_url, stream=True).raw) |
| img = img.convert('RGB') |
| st.image(img) |
| img.save('tmp.jpg') |
| predict() |
| os.remove('tmp.jpg') |
| |
| st.markdown('<center style="opacity: 70%">OR</center>', unsafe_allow_html=True) |
| img_upload = st.file_uploader(label='Upload Image', type=['jpg', 'png', 'jpeg']) |
| |
| if img_upload != None: |
| img = img_upload.read() |
| img = Image.open(io.BytesIO(img)) |
| img = img.convert('RGB') |
| img.save('tmp.jpg') |
| st.image(img) |
| predict() |
| os.remove('tmp.jpg')''' |
