v1.3.4

.github/workflows/release.yml

@@ -0,0 +1,41 @@
+name: release
+on:
+  push:
+    tags:
+      - '*'
+
+jobs:
+  build:
+    permissions: write-all
+    name: Create Release
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v2
+      - name: Create Release
+        id: create_release
+        uses: actions/create-release@v1
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        with:
+          tag_name: ${{ github.ref }}
+          release_name: GFPGAN ${{ github.ref }} Release Note
+          body: |
+            🚀 See you again 😸
+            🚀Have a nice day 😸 and happy everyday 😃
+            🚀 Long time no see ☄️
+
+            ✨ **Highlights**
+            ✅ [Features] Support ...
+
+            🐛 **Bug Fixes**
+
+            🌴 **Improvements**
+
+            📢📢📢
+
+            <p align="center">
+               <img src="https://raw.githubusercontent.com/TencentARC/GFPGAN/master/assets/gfpgan_logo.png" height=150>
+            </p>
+          draft: true
+          prerelease: false

VERSION

@@ -1 +1 @@
-1.3.2
+1.3.4

gfpgan/models/gfpgan_model.py

@@ -3,7 +3,7 @@ import os.path as osp
 import torch
 from basicsr.archs import build_network
 from basicsr.losses import build_loss
-from basicsr.losses.losses import r1_penalty
+from basicsr.losses.gan_loss import r1_penalty
 from basicsr.metrics import calculate_metric
 from basicsr.models.base_model import BaseModel
 from basicsr.utils import get_root_logger, imwrite, tensor2img

gfpgan/utils.py

@@ -29,12 +29,12 @@ class GFPGANer():
         bg_upsampler (nn.Module): The upsampler for the background. Default: None.
     """
 
-    def __init__(self, model_path, upscale=2, arch='clean', channel_multiplier=2, bg_upsampler=None):
+    def __init__(self, model_path, upscale=2, arch='clean', channel_multiplier=2, bg_upsampler=None, device=None):
         self.upscale = upscale
         self.bg_upsampler = bg_upsampler
 
         # initialize model
-        self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+        self.device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') if device is None else device
         # initialize the GFP-GAN
         if arch == 'clean':
             self.gfpgan = GFPGANv1Clean(
@@ -79,6 +79,7 @@ class GFPGANer():
             crop_ratio=(1, 1),
             det_model='retinaface_resnet50',
             save_ext='png',
+            use_parse=True,
             device=self.device)
 
         if model_path.startswith('https://'):

requirements.txt

@@ -1,12 +1,12 @@
-torch>=1.7
+basicsr>=1.3.4.0
+facexlib>=0.2.3
+lmdb
 numpy<1.21  # numba requires numpy<1.21,>=1.17
 opencv-python
-torchvision
-scipy
-tqdm
-basicsr>=1.3.4.0
-facexlib>=0.2.0.3
-lmdb
 pyyaml
+scipy
 tb-nightly
+torch>=1.7
+torchvision
+tqdm
 yapf