Update app.py

app.py

@@ -1,62 +1,62 @@
-import streamlit as st
-import numpy as np
-import cv2
-from PIL import Image
-
-# Load model files
-prototxt_path = "colorization_deploy_v2.prototxt"
-model_path = "colorization_release_v2.caffemodel"
-kernel_path = "pts_in_hull.npy"
-
-# Load the model
-net = cv2.dnn.readNetFromCaffe(prototxt_path, model_path)
-points = np.load(kernel_path)
-points = points.transpose().reshape(2, 313, 1, 1)
-net.getLayer(net.getLayerId("class8_ab")).blobs = [points.astype(np.float32)]
-net.getLayer(net.getLayerId("conv8_313_rh")).blobs = [np.full([1, 313], 2.686, dtype="float32")]
-
-# Streamlit App
-st.title("Black-and-White Image Colorization")
-st.write("Upload a black-and-white image to colorize it.")
-
-uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
-
-if uploaded_file is not None:
-    # Convert uploaded file to OpenCV format
-    image = Image.open(uploaded_file)
-    bw_image = np.array(image.convert("RGB"))
-    bw_image = cv2.cvtColor(bw_image, cv2.COLOR_RGB2BGR)
-
-    # Preprocessing for colorization
-    normalized = bw_image.astype("float32") / 255.0
-    lab = cv2.cvtColor(normalized, cv2.COLOR_BGR2LAB)
-    resized = cv2.resize(lab, (224, 224))
-    L = cv2.split(resized)[0]
-    L -= 55
-
-    # Predict color channels
-    net.setInput(cv2.dnn.blobFromImage(L))
-    ab = net.forward()[0, :, :, :].transpose((1, 2, 0))
-    ab = cv2.resize(ab, (bw_image.shape[1], bw_image.shape[0]))
-
-    # Combine L and ab channels
-    L = cv2.split(lab)[0]
-    colorized = np.concatenate((L[:, :, np.newaxis], ab), axis=2)
-
-    # Convert LAB to BGR
-    colorized = cv2.cvtColor(colorized, cv2.COLOR_LAB2BGR)
-    colorized = (255 * colorized).astype("uint8")
-
-    # Display results
-    st.image(colorized, channels="BGR", caption="Colorized Image")
-
-    # Provide download link
-    colorized_image = Image.fromarray(cv2.cvtColor(colorized, cv2.COLOR_BGR2RGB))
-    colorized_image.save("colorized_output.jpg")
-    with open("colorized_output.jpg", "rb") as file:
-        btn = st.download_button(
-            label="Download colorized image",
-            data=file,
-            file_name="colorized_image.jpg",
-            mime="image/jpeg"
-        )
+import streamlit as st
+import numpy as np
+import cv2
+from PIL import Image
+
+# Load model files
+prototxt_path = "colorization_deploy_v2.prototxt"
+model_path = "colorization_release_v2.caffemodel"
+kernel_path = "pts_in_hull.npy"
+
+# Load the model
+net = cv2.dnn.readNetFromCaffe(prototxt_path, model_path)
+points = np.load(kernel_path)
+points = points.transpose().reshape(2, 313, 1, 1)
+net.getLayer(net.getLayerId("class8_ab")).blobs = [points.astype(np.float32)]
+net.getLayer(net.getLayerId("conv8_313_rh")).blobs = [np.full([1, 313], 2.686, dtype="float32")]
+
+# Streamlit App
+st.title("Black-and-White Image Colorization")
+st.write("Upload a black-and-white image to colorize it.")
+
+uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+
+if uploaded_file is not None:
+    # Convert uploaded file to OpenCV format
+    image = Image.open(uploaded_file)
+    bw_image = np.array(image.convert("RGB"))
+    bw_image = cv2.cvtColor(bw_image, cv2.COLOR_RGB2BGR)
+
+    # Preprocessing for colorization
+    normalized = bw_image.astype("float32") / 255.0
+    lab = cv2.cvtColor(normalized, cv2.COLOR_BGR2LAB)
+    resized = cv2.resize(lab, (224, 224))
+    L = cv2.split(resized)[0]
+    L -= 50
+
+    # Predict color channels
+    net.setInput(cv2.dnn.blobFromImage(L))
+    ab = net.forward()[0, :, :, :].transpose((1, 2, 0))
+    ab = cv2.resize(ab, (bw_image.shape[1], bw_image.shape[0]))
+
+    # Combine L and ab channels
+    L = cv2.split(lab)[0]
+    colorized = np.concatenate((L[:, :, np.newaxis], ab), axis=2)
+
+    # Convert LAB to BGR
+    colorized = cv2.cvtColor(colorized, cv2.COLOR_LAB2BGR)
+    colorized = (255 * colorized).astype("uint8")
+
+    # Display results
+    st.image(colorized, channels="BGR", caption="Colorized Image")
+
+    # Provide download link
+    colorized_image = Image.fromarray(cv2.cvtColor(colorized, cv2.COLOR_BGR2RGB))
+    colorized_image.save("colorized_output.jpg")
+    with open("colorized_output.jpg", "rb") as file:
+        btn = st.download_button(
+            label="Download colorized image",
+            data=file,
+            file_name="colorized_image.jpg",
+            mime="image/jpeg"
+        )