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.gitattributes

@@ -33,3 +33,4 @@ 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
+output.png filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,34 @@
+import os
+import cv2
+import tempfile
+from modelscope.outputs import OutputKeys
+from modelscope.pipelines import pipeline
+from modelscope.utils.constant import Tasks
+import PIL
+from pathlib import Path
+import gradio as gr
+import numpy as np
+
+"""Load the model into memory to make running multiple predictions efficient"""
+img_colorization = pipeline(Tasks.image_colorization, model='iic/cv_ddcolor_image-colorization')
+
+
+def inference(img):
+    image = cv2.imread(str(img))
+
+    output = img_colorization(image[..., ::-1])
+    result = output[OutputKeys.OUTPUT_IMG].astype(np.uint8)
+
+    temp_dir = tempfile.mkdtemp()
+    out_path = os.path.join(temp_dir, 'old-to-color.png')
+    cv2.imwrite(out_path, result)
+    return Path(out_path)
+
+
+title = "Color Restorization Model"
+gr.Interface(
+    inference,
+    [gr.inputs.Image(type="filepath", label="Input")],
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title
+).launch(enable_queue=True)

requirements.txt

@@ -0,0 +1,6 @@
+modelscope
+Pillow
+numpy
+torch
+sentencepiece
+timm