Upload 5 files

.gitattributes

@@ -32,3 +32,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+CADET.hdf5 filter=lfs diff=lfs merge=lfs -text

CADET.hdf5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b2f01be82295c74f412fb77b74155f6c4e971bf62fe956f646e83f1636fadaa6
+size 7423136

README.md

@@ -1,9 +1,11 @@
 ---
-title: CADET
-emoji: 🦀
-colorFrom: gray
-colorTo: blue
-sdk: docker
+title: CADET Streamlit
+emoji: 🔥
+colorFrom: pink
+colorTo: pink
+sdk: streamlit
+sdk_version: 1.17.0
+app_file: app.py
 pinned: false
 ---
 

app.py

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+import streamlit as st
+import numpy as np
+import matplotlib.pyplot as plt
+from astropy.io import fits
+from astropy.wcs import WCS
+from astropy.nddata import Cutout2D
+from tensorflow.keras.models import load_model
+
+st.set_option('deprecation.showPyplotGlobalUse', False)
+
+st.title("FITS Image Viewer")
+
+model = load_model("CADET.hdf5")
+
+# Define function to plot the uploaded image
+def plot_image(image_array, pred):
+    plt.figure(figsize=(10, 5))
+    plt.subplot(1, 2, 1)
+    plt.imshow(image_array, origin="lower")
+    plt.axis('off')
+
+    plt.subplot(1, 2, 2)
+    plt.imshow(pred, origin="lower")
+    plt.axis('off')
+    st.pyplot()
+
+def cut(data0, wcs0, scale=1):
+   shape = data0.shape[0]
+   x0 = shape / 2
+   size = 128 * scale
+   cutout = Cutout2D(data0, (x0, x0), (size, size), wcs=wcs0)
+   return cutout.data, cutout.wcs
+
+# Create file uploader widget
+uploaded_file = st.file_uploader("Choose a FITS file", type=['fits'])
+
+# If file is uploaded, read in the data and plot it
+if uploaded_file is not None:
+    with fits.open(uploaded_file) as hdul:
+        data = hdul[0].data
+        wcs = WCS(hdul[0].header)
+        data, wcs = cut(data, wcs, scale=1)
+
+        image_data = np.log10(data+1)
+        pred = model.predict(image_data.reshape(1, 128, 128, 1)).reshape(128 ,128)
+
+        plot_image(image_data, pred)

requirements.txt

@@ -0,0 +1,6 @@
+matplotlib==3.5.3
+numpy==1.23.2
+scipy==1.9.0
+astropy==5.0.4
+keras==2.8.0
+tensorflow==2.8.1