Spaces:
Runtime error
Runtime error
File size: 1,976 Bytes
f527373 05d4c3b f527373 8a55d9d e2a98c2 f527373 1c31448 f527373 d3d8066 3ed339a a79b50e d3d8066 8a55d9d b5bd9ee d3d8066 5da6813 d3d8066 c313dd0 5da6813 d3d8066 5da6813 f527373 c0996a6 05eb182 c313dd0 05eb182 2869667 f094fcd |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 |
import ast
import os
import requests
from PIL import Image
import streamlit as st
import io
api = "https://56dd-188-130-155-168.ngrok-free.app"
st.set_page_config(layout="wide")
st.title("Stamp2vec 📄")
input_image = st.file_uploader("insert image")
if(input_image):
image = Image.open(input_image)
st.header("Original")
st.image(input_image, use_column_width=True)
detection_model = st.selectbox("Select detection model", ("YOLO-stamp", ))
embedding_model = st.selectbox("Select embedding model", ("vits8", ))
if st.button("Get prediction"):
with st.spinner("Loading..."):
response = requests.post(os.path.join(api, f"bounding-boxes-{detection_model}/"),
files = {"file": input_image.getvalue(), "model_id": detection_model})
prediction = ast.literal_eval(response.text)
response = requests.post(os.path.join(api, f"image-w-boxes-{detection_model}/"),
files = {"file": input_image.getvalue(), "model_id": detection_model})
image_with_boxes = response.content
arr = []
for b in prediction["bboxes"]:
stamp = image.crop((b["xmin"], b["ymin"], b["xmin"] + b["width"], b["ymin"] + b["height"]))
output = io.BytesIO()
stamp.save(output, format="BMP")
response = ast.literal_eval(requests.post(os.path.join(api, f"embeddings-from-cropped-{embedding_model}/"),
files = {"file": output.getvalue(), "model_id": embedding_model}).text)
arr.extend(response["embedding"])
col1, col2, col3 = st.columns(3)
col1.subheader("Prediction")
col1.write(prediction)
col2.subheader("Image")
col2.image(image_with_boxes, use_column_width=True)
col3.subheader("Embeddings")
col3.write(arr) |