make api

.gitignore

@@ -0,0 +1,8 @@
+*.png
+*.jpg
+.idea/
+__pycache__/
+flagged
+gfpgan
+output
+

app.py

@@ -7,24 +7,14 @@ from basicsr.archs.srvgg_arch import SRVGGNetCompact
 from gfpgan.utils import GFPGANer
 from huggingface_hub import snapshot_download, hf_hub_download
 from realesrgan.utils import RealESRGANer
+import examples
 
 REALESRGAN_REPO_ID = 'leonelhs/realesrgan'
 GFPGAN_REPO_ID = 'leonelhs/gfpgan'
 
 os.system("pip freeze")
 
-torch.hub.download_url_to_file(
-    'https://upload.wikimedia.org/wikipedia/commons/thumb/a/ab/Abraham_Lincoln_O-77_matte_collodion_print.jpg/1024px-Abraham_Lincoln_O-77_matte_collodion_print.jpg',
-    'lincoln.jpg')
-torch.hub.download_url_to_file(
-    'https://user-images.githubusercontent.com/17445847/187400315-87a90ac9-d231-45d6-b377-38702bd1838f.jpg',
-    'AI-generate.jpg')
-torch.hub.download_url_to_file(
-    'https://user-images.githubusercontent.com/17445847/187400981-8a58f7a4-ef61-42d9-af80-bc6234cef860.jpg',
-    'Blake_Lively.jpg')
-torch.hub.download_url_to_file(
-    'https://user-images.githubusercontent.com/17445847/187401133-8a3bf269-5b4d-4432-b2f0-6d26ee1d3307.png',
-    '10045.png')
+examples.download()
 
 # background enhancer with RealESRGAN
 model = SRVGGNetCompact(num_in_ch=3, num_out_ch=3, num_feat=64, num_conv=32, upscale=4, act_type='prelu')
@@ -36,7 +26,7 @@ os.makedirs('output', exist_ok=True)
 
 
 # def inference(img, version, scale, weight):
-def inference(img, version, scale):
+def predict(img, version, scale):
     # weight /= 100
     print(img, version, scale)
     if scale > 4:
@@ -125,12 +115,10 @@ If you have any question, please email 📧 `[email protected]` or `xintao
 <center><img src='https://visitor-badge.glitch.me/badge?page_id=Gradio_Xintao_GFPGAN' alt='visitor badge'></center>
 """
 demo = gr.Interface(
-    inference, [
+    predict, [
         gr.Image(type="filepath", label="Input"),
-        # gr.Radio(['v1.2', 'v1.3', 'v1.4', 'RestoreFormer', 'CodeFormer'], type="value", value='v1.4', label='version'),
         gr.Radio(['v1.2', 'v1.3', 'v1.4', 'RestoreFormer'], type="value", value='v1.4', label='version'),
         gr.Number(label="Rescaling factor", value=2),
-        # gr.Slider(0, 100, label='Weight, only for CodeFormer. 0 for better quality, 100 for better identity', value=50)
     ], [
         gr.Image(type="numpy", label="Output (The whole image)"),
         gr.File(label="Download the output image")

examples.py

@@ -0,0 +1,25 @@
+import torch
+
+examples = [
+    {
+        'name': 'lincoln.jpg',
+        'url': 'https://upload.wikimedia.org/wikipedia/commons/thumb/a/ab/Abraham_Lincoln_O-77_matte_collodion_print.jpg/1024px-Abraham_Lincoln_O-77_matte_collodion_print.jpg'
+    },
+    {
+        'name': 'AI-generate.jpg',
+        'url': 'https://user-images.githubusercontent.com/17445847/187400315-87a90ac9-d231-45d6-b377-38702bd1838f.jpg'
+    },
+    {
+        'name': 'Blake_Lively.jpg',
+        'url': 'https://user-images.githubusercontent.com/17445847/187400981-8a58f7a4-ef61-42d9-af80-bc6234cef860.jpg'
+    },
+    {
+        'name': '10045.png',
+        'url': 'https://user-images.githubusercontent.com/17445847/187401133-8a3bf269-5b4d-4432-b2f0-6d26ee1d3307.png'
+    }
+]
+
+
+def download():
+    for example in examples:
+        torch.hub.download_url_to_file(example['url'], example['name'])