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# -*- coding: utf-8 -*- | |
""" | |
Created on Fri Nov 25 21:37:33 2022 | |
@author: Bharathraj C L | |
""" | |
import deepdoctection | |
import streamlit as st | |
import mmcv | |
import os | |
import numpy as np | |
from PIL import Image | |
from mmdet.apis import init_detector, inference_detector, show_result_pyplot | |
from pathlib import Path | |
st.set_option('deprecation.showPyplotGlobalUse', False) | |
st.title("Table Detection from Images") | |
config_file = 'cascade_mask_rcnn_hrnetv2p_w32_20e.py' | |
checkpoint_file = 'epoch_36.pth' | |
model = init_detector(config_file, checkpoint_file, device='cuda:0') | |
uploaded_file = st.file_uploader("Choose an image...", type="jpg") | |
if uploaded_file is not None: | |
image = Image.open(uploaded_file) | |
st.image(image, caption='Uploaded Image.', use_column_width=True) | |
directory = "tempDir" | |
path = os.path.join(os.getcwd(), directory) | |
p = Path(path) | |
if not p.exists(): | |
os.mkdir(p) | |
with open(os.path.join(path, uploaded_file.name),"wb") as f: | |
f.write(uploaded_file.getbuffer()) | |
file_loc = os.path.join(path, uploaded_file.name) | |
result = inference_detector(model, file_loc) | |
st.pyplot(show_result_pyplot(file_loc, result,('Bordered', 'cell', 'Borderless'), score_thr=0.85)) | |