Use HF Hub download

app.py

@@ -3,15 +3,24 @@ import json
 import os
 
 import gradio as gr
-from gradio_dualvision import DualVisionApp
-from gradio_dualvision.gradio_patches.radio import Radio
 from PIL import Image
 import numpy as np
 
+from gradio_dualvision import DualVisionApp
+from gradio_dualvision.gradio_patches.radio import Radio
+from huggingface_hub import hf_hub_download
 from model import build_thera
 from super_resolve import process
 
-CHECKPOINT = "checkpoints/thera-edsr-plus.pkl"
+REPO_ID = "prs-eth/thera-edsr-plus"
+
+# load model
+model_path = hf_hub_download(repo_id=REPO_ID, filename="model.pkl")
+with open(model_path, 'rb') as fh:
+    check = pickle.load(fh)
+    params, backbone, size = check['model'], check['backbone'], check['size']
+
+model = build_thera(3, backbone, size)
 
 
 class TheraApp(DualVisionApp):
@@ -73,13 +82,6 @@ class TheraApp(DualVisionApp):
             round(source.shape[1] * scale),
         )
 
-        # load model
-        with open(CHECKPOINT, 'rb') as fh:
-            check = pickle.load(fh)
-            params, backbone, size = check['model'], check['backbone'], check['size']
-
-        model = build_thera(3, backbone, size)
-
         out = process(source, model, params, target_shape, do_ensemble=do_ensemble)
         out = Image.fromarray(np.asarray(out))
 

checkpoints/thera-edsr-plus.pkl

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:a805ca6f0486d9eba8f228200340a0e6aedde16529e11fc7b98dc26d830d9aa8
-size 31632862