File size: 1,064 Bytes
8dfcc25 b1e0561 8dfcc25 |
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 |
import streamlit as st
import numpy as np
import cv2
from keras.models import model_from_json
def read_image(image_file):
image = cv2.imdecode(np.fromstring(image_file.read(), np.uint8), cv2.IMREAD_COLOR)
image = cv2.resize(image, (512, 512))
image = image / 255.0
image = image.astype(np.float32)
return image
with open("model.json", "r") as json_file:
model_json = json_file.read()
model = model_from_json(model_json)
model.load_weights("model.h5")
st.title("Image Segmentation App")
uploaded_file = st.file_uploader("Upload an image for segmentation...", type=["jpg", "jpeg", "png"])
if uploaded_file is not None:
image = read_image(uploaded_file)
image = np.expand_dims(image, axis=0)
y_pred = model.predict(image)[0]
y_pred = y_pred > 0.5
y_pred = y_pred.astype(np.uint8) * 255
col1, col2 = st.columns(2)
with col1:
st.image(uploaded_file, caption="Original Image", use_column_width=True)
with col2:
st.image(y_pred, caption="Predicted Segmentation Mask", use_column_width=True) |