codeformer support

1 files changed, 108 insertions, 0 deletions

diff --git a/modules/codeformer_model.py b/modules/codeformer_model.py
new file mode 100644
index 00000000..836417c2
--- /dev/null
+++ b/modules/codeformer_model.py
@@ -0,0 +1,108 @@
+import os

+import sys

+import traceback

+import torch

+

+from modules import shared

+from modules.paths import script_path

+import modules.shared

+import modules.face_restoration

+from importlib import reload

+

+# codeformer people made a choice to include modified basicsr librry to their projectwhich makes

+# it utterly impossiblr to use it alongside with other libraries that also use basicsr, like GFPGAN.

+# I am making a choice to include some files from codeformer to work around this issue.

+

+pretrain_model_url = 'https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth'

+

+have_codeformer = False

+

+def setup_codeformer():

+    path = modules.paths.paths.get("CodeFormer", None)

+    if path is None:

+        return

+

+

+    # both GFPGAN and CodeFormer use bascisr, one has it installed from pip the other uses its own

+    #stored_sys_path = sys.path

+    #sys.path = [path] + sys.path

+

+    try:

+        from torchvision.transforms.functional import normalize

+        from modules.codeformer.codeformer_arch import CodeFormer

+        from basicsr.utils.download_util import load_file_from_url

+        from basicsr.utils import imwrite, img2tensor, tensor2img

+        from facelib.utils.face_restoration_helper import FaceRestoreHelper

+        from modules.shared import cmd_opts

+

+        net_class = CodeFormer

+

+        class FaceRestorerCodeFormer(modules.face_restoration.FaceRestoration):

+            def name(self):

+                return "CodeFormer"

+

+            def __init__(self):

+                self.net = None

+                self.face_helper = None

+

+            def create_models(self):

+

+                if self.net is not None and self.face_helper is not None:

+                    return self.net, self.face_helper

+

+                net = net_class(dim_embd=512, codebook_size=1024, n_head=8, n_layers=9, connect_list=['32', '64', '128', '256']).to(shared.device)

+                ckpt_path = load_file_from_url(url=pretrain_model_url, model_dir=os.path.join(path, 'weights/CodeFormer'), progress=True)

+                checkpoint = torch.load(ckpt_path)['params_ema']

+                net.load_state_dict(checkpoint)

+                net.eval()

+

+                face_helper = FaceRestoreHelper(1, face_size=512, crop_ratio=(1, 1), det_model='retinaface_resnet50', save_ext='png', use_parse=True, device=shared.device)

+

+                if not cmd_opts.unload_gfpgan:

+                    self.net = net

+                    self.face_helper = face_helper

+

+                return net, face_helper

+

+            def restore(self, np_image):

+                np_image = np_image[:, :, ::-1]

+

+                net, face_helper = self.create_models()

+                face_helper.clean_all()

+                face_helper.read_image(np_image)

+                face_helper.get_face_landmarks_5(only_center_face=False, resize=640, eye_dist_threshold=5)

+                face_helper.align_warp_face()

+

+                for idx, cropped_face in enumerate(face_helper.cropped_faces):

+                    cropped_face_t = img2tensor(cropped_face / 255., bgr2rgb=True, float32=True)

+                    normalize(cropped_face_t, (0.5, 0.5, 0.5), (0.5, 0.5, 0.5), inplace=True)

+                    cropped_face_t = cropped_face_t.unsqueeze(0).to(shared.device)

+

+                    try:

+                        with torch.no_grad():

+                            output = net(cropped_face_t, w=shared.opts.code_former_weight, adain=True)[0]

+                            restored_face = tensor2img(output, rgb2bgr=True, min_max=(-1, 1))

+                        del output

+                        torch.cuda.empty_cache()

+                    except Exception as error:

+                        print(f'\tFailed inference for CodeFormer: {error}', file=sys.stderr)

+                        restored_face = tensor2img(cropped_face_t, rgb2bgr=True, min_max=(-1, 1))

+

+                    restored_face = restored_face.astype('uint8')

+                    face_helper.add_restored_face(restored_face)

+

+                face_helper.get_inverse_affine(None)

+

+                restored_img = face_helper.paste_faces_to_input_image()

+                restored_img = restored_img[:, :, ::-1]

+                return restored_img

+

+        global have_codeformer

+        have_codeformer = True

+        shared.face_restorers.append(FaceRestorerCodeFormer())

+

+    except Exception:

+        print("Error setting up CodeFormer:", file=sys.stderr)

+        print(traceback.format_exc(), file=sys.stderr)

+

+   # sys.path = stored_sys_path