Merge pull request #4637 from CalamitousFelicitousness/refactor/remove-face-restoration

Refactor/remove face restoration

scripts/postprocessing_codeformer.py

@@ -1,28 +0,0 @@
-from PIL import Image
-import numpy as np
-import gradio as gr
-from modules import scripts_postprocessing
-from modules.postprocess import codeformer_model
-
-
-class ScriptPostprocessingCodeFormer(scripts_postprocessing.ScriptPostprocessing):
-    name = "CodeFormer"
-    order = 3000
-
-    def ui(self):
-        with gr.Accordion('Restore faces: CodeFormer', open = False, elem_id="postprocess_codeformer_accordion"):
-            with gr.Row():
-                codeformer_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label="Strength", value=0.0, elem_id="extras_codeformer_visibility")
-                codeformer_weight = gr.Slider(minimum=0.0, maximum=1.0, step=0.01, label="Weight", value=0.2, elem_id="extras_codeformer_weight")
-        return { "codeformer_visibility": codeformer_visibility, "codeformer_weight": codeformer_weight }
-
-    def process(self, pp: scripts_postprocessing.PostprocessedImage, codeformer_visibility, codeformer_weight): # pylint: disable=arguments-differ
-        if codeformer_visibility == 0:
-            return
-        restored_img = codeformer_model.codeformer.restore(np.array(pp.image, dtype=np.uint8), w=codeformer_weight)
-        res = Image.fromarray(restored_img)
-        if codeformer_visibility < 1.0:
-            res = Image.blend(pp.image, res, codeformer_visibility)
-        pp.image = res
-        pp.info["CodeFormer visibility"] = round(codeformer_visibility, 3)
-        pp.info["CodeFormer weight"] = round(codeformer_weight, 3)

scripts/postprocessing_gfpgan.py

@@ -1,29 +0,0 @@
-from PIL import Image
-import numpy as np
-import gradio as gr
-from modules import scripts_postprocessing
-
-
-class ScriptPostprocessingGfpGan(scripts_postprocessing.ScriptPostprocessing):
-    name = "GFPGAN"
-    order = 2000
-
-    def ui(self):
-        with gr.Accordion('Restore faces: GFPGan', open = False, elem_id="postprocess_gfpgan_accordion"):
-            with gr.Row():
-                gfpgan_visibility = gr.Slider(minimum=0.0, maximum=1.0, step=0.001, label="Strength", value=0, elem_id="extras_gfpgan_visibility")
-        return { "gfpgan_visibility": gfpgan_visibility }
-
-    def process(self, pp: scripts_postprocessing.PostprocessedImage, gfpgan_visibility): # pylint: disable=arguments-differ
-        from installer import install
-        install("facexlib")
-        install("gfpgan")
-        if gfpgan_visibility == 0:
-            return
-        from modules.postprocess import gfpgan_model
-        restored_img = gfpgan_model.gfpgan_fix_faces(np.array(pp.image, dtype=np.uint8))
-        res = Image.fromarray(restored_img)
-        if gfpgan_visibility < 1.0:
-            res = Image.blend(pp.image, res, gfpgan_visibility)
-        pp.image = res
-        pp.info["GFPGAN visibility"] = round(gfpgan_visibility, 3)

scripts/xyz/xyz_grid_classes.py

@@ -246,7 +246,7 @@ axis_options = [
     AxisOption("[Refine] Refiner steps", float, apply_field("refiner_steps")),
     AxisOption("[Postprocess] Upscaler", str, apply_upscaler, cost=0.4, choices=lambda: [x.name for x in shared.sd_upscalers]),
     AxisOption("[Postprocess] Context", str, apply_context, choices=lambda: ["Add with forward", "Remove with forward", "Add with backward", "Remove with backward"]),
-    AxisOption("[Postprocess] Detailer", str, apply_detailer, fmt=format_value_add_label),
+    AxisOption("[Postprocess] Detailer", bool, apply_detailer, fmt=format_bool, choices=lambda: [False, True]),
     AxisOption("[Postprocess] Detailer strength", str, apply_field("detailer_strength")),
     AxisOption("[Quant] SDNQ quant mode", str, apply_sdnq_quant, cost=0.9, fmt=format_value_add_label, choices=lambda: ['none'] + sorted(shared.sdnq_quant_modes)),
     AxisOption("[Quant] SDNQ quant mode TE", str, apply_sdnq_quant_te, cost=0.9, fmt=format_value_add_label, choices=lambda: ['none'] + sorted(shared.sdnq_quant_modes)),

scripts/xyz/xyz_grid_shared.py

@@ -284,17 +284,8 @@ def apply_context(p: processing.StableDiffusionProcessingTxt2Img, opt, x):
 
 
 def apply_detailer(p, opt, x):
-    opt = opt.lower()
-    if opt == 'codeformer':
-        is_active = True
-        p.detailer_model = 'CodeFormer'
-    elif opt == 'gfpgan':
-        is_active = True
-        p.detailer_model = 'GFPGAN'
-    else:
-        is_active = opt in ('true', 'yes', 'y', '1')
-    p.detailer_enabled = is_active
-    shared.log.debug(f'XYZ grid apply face-restore: "{x}"')
+    p.detailer_enabled = bool(opt)
+    shared.log.debug(f'XYZ grid apply detailer: "{x}"')
 
 
 def apply_control(field):

scripts/xyz_grid_on.py

@@ -452,7 +452,6 @@ class Script(scripts_manager.Script):
 
     def process_images(self, p, *args): # pylint: disable=W0221, W0613
         if xyz_results_cache is not None and len(xyz_results_cache.images) > 0:
-            p.restore_faces = False
             p.detailer_enabled = False
             p.color_corrections = None
             # p.scripts = None