Move all choices to one file

roop/choices.py

@@ -0,0 +1,10 @@
+from typing import List
+
+from roop.typing import FaceRecognition, FaceAnalyserDirection, FaceAnalyserAge, FaceAnalyserGender, TempFrameFormat, OutputVideoEncoder
+
+face_recognition: List[FaceRecognition] = ['reference', 'many']
+face_analyser_direction: List[FaceAnalyserDirection] = ['left-right', 'right-left', 'top-bottom', 'bottom-top', 'small-large', 'large-small']
+face_analyser_age: List[FaceAnalyserAge] = ['child', 'teen', 'adult', 'senior']
+face_analyser_gender: List[FaceAnalyserGender] = ['male', 'female']
+temp_frame_format: List[TempFrameFormat] = ['jpg', 'png']
+output_video_encoder: List[OutputVideoEncoder] = ['libx264', 'libx265', 'libvpx-vp9', 'h264_nvenc', 'hevc_nvenc']

roop/core.py

@@ -16,6 +16,7 @@
 import tensorflow
 
 
+import roop.choices
 import roop.globals
 import roop.metadata
 from roop.predictor import predict_image, predict_video
@@ -37,22 +38,22 @@ def parse_args() -> None:
     program.add_argument('--keep-fps', help='keep target fps', dest='keep_fps', action='store_true')
     program.add_argument('--keep-temp', help='keep temporary frames', dest='keep_temp', action='store_true')
     program.add_argument('--skip-audio', help='skip target audio', dest='skip_audio', action='store_true')
-    program.add_argument('--face-recognition', help='face recognition method', dest='face_recognition', default='reference', choices=['reference', 'many'])
-    program.add_argument('--face-analyser-direction', help='direction used for the face analyser', dest='face_analyser_direction', default='left-right', choices=['left-right', 'right-left', 'top-bottom', 'bottom-top', 'small-large', 'large-small'])
-    program.add_argument('--face-analyser-age', help='age used for the face analyser', dest='face_analyser_age', choices=['child', 'teen', 'adult', 'senior'])
-    program.add_argument('--face-analyser-gender', help='gender used for the face analyser', dest='face_analyser_gender', choices=['male', 'female'])
+    program.add_argument('--face-recognition', help='face recognition method', dest='face_recognition', default='reference', choices=roop.choices.face_recognition)
+    program.add_argument('--face-analyser-direction', help='direction used for the face analyser', dest='face_analyser_direction', default='left-right', choices=roop.choices.face_analyser_direction)
+    program.add_argument('--face-analyser-age', help='age used for the face analyser', dest='face_analyser_age', choices=roop.choices.face_analyser_age)
+    program.add_argument('--face-analyser-gender', help='gender used for the face analyser', dest='face_analyser_gender', choices=roop.choices.face_analyser_gender)
     program.add_argument('--reference-face-position', help='position of the reference face', dest='reference_face_position', type=int, default=0)
     program.add_argument('--reference-face-distance', help='distance between reference face and target face', dest='reference_face_distance', type=float, default=1.5)
     program.add_argument('--reference-frame-number', help='number of the reference frame', dest='reference_frame_number', type=int, default=0)
     program.add_argument('--trim-frame-start', help='start frame use for extraction', dest='trim_frame_start', type=int)
     program.add_argument('--trim-frame-end', help='end frame use for extraction', dest='trim_frame_end', type=int)
-    program.add_argument('--temp-frame-format', help='image format used for frame extraction', dest='temp_frame_format', default='jpg', choices=['jpg', 'png'])
+    program.add_argument('--temp-frame-format', help='image format used for frame extraction', dest='temp_frame_format', default='jpg', choices=roop.choices.temp_frame_format)
     program.add_argument('--temp-frame-quality', help='image quality used for frame extraction', dest='temp_frame_quality', type=int, default=100, choices=range(101), metavar='[0-100]')
-    program.add_argument('--output-video-encoder', help='encoder used for the output video', dest='output_video_encoder', default='libx264', choices=['libx264', 'libx265', 'libvpx-vp9', 'h264_nvenc', 'hevc_nvenc'])
+    program.add_argument('--output-video-encoder', help='encoder used for the output video', dest='output_video_encoder', default='libx264', choices=roop.choices.output_video_encoder)
     program.add_argument('--output-video-quality', help='quality used for the output video', dest='output_video_quality', type=int, default=90, choices=range(101), metavar='[0-100]')
     program.add_argument('--max-memory', help='maximum amount of RAM in GB', dest='max_memory', type=int)
-    program.add_argument('--execution-providers', help='list of available execution providers (choices: cpu, ...)', dest='execution_providers', default=['cpu'], choices=suggest_execution_providers(), nargs='+')
-    program.add_argument('--execution-thread-count', help='number of execution threads', dest='execution_thread_count', type=int, default=suggest_execution_thread_count())
+    program.add_argument('--execution-providers', help='list of available execution providers (choices: cpu, ...)', dest='execution_providers', default=['cpu'], choices=suggest_execution_providers_choices(), nargs='+')
+    program.add_argument('--execution-thread-count', help='number of execution threads', dest='execution_thread_count', type=int, default=suggest_execution_thread_count_default())
     program.add_argument('--execution-queue-count', help='number of execution queries', dest='execution_queue_count', type=int,  default=1)
     program.add_argument('-v', '--version', action='version', version=f'{roop.metadata.name} {roop.metadata.version}')
 
@@ -86,15 +87,15 @@ def parse_args() -> None:
     roop.globals.execution_queue_count = args.execution_queue_count
 
 
-def suggest_execution_providers() -> List[str]:
+def suggest_execution_providers_choices() -> List[str]:
     return encode_execution_providers(onnxruntime.get_available_providers())
 
 
-def suggest_ui_layouts() -> List[str]:
+def suggest_ui_layouts_choices() -> List[str]:
     return list_module_names('roop/uis/__layouts__')
 
 
-def suggest_execution_thread_count() -> int:
+def suggest_execution_thread_count_default() -> int:
     if 'CUDAExecutionProvider' in onnxruntime.get_available_providers():
         return 8
     return 1

roop/processors/frame/core.py

@@ -32,7 +32,7 @@ def load_frame_processor_module(frame_processor: str) -> Any:
             if not hasattr(frame_processor_module, method_name):
                 raise NotImplementedError
     except ModuleNotFoundError:
-        sys.exit(f'Frame processor {frame_processor} could be not loaded.')
+        sys.exit(f'Frame processor {frame_processor} could not be loaded.')
     except NotImplementedError:
         sys.exit(f'Frame processor {frame_processor} not implemented correctly.')
     return frame_processor_module

roop/uis/__components__/face_analyser.py

@@ -2,6 +2,7 @@
 
 import gradio
 
+import roop.choices
 import roop.globals
 from roop.uis import core as ui
 from roop.uis.typing import Update
@@ -20,17 +21,17 @@ def render() -> None:
         with gradio.Row():
             FACE_ANALYSER_DIRECTION_DROPDOWN = gradio.Dropdown(
                 label='FACE ANALYSER DIRECTION',
-                choices=['left-right', 'right-left', 'top-bottom', 'bottom-top', 'small-large', 'large-small'],
-                value=roop.globals.face_analyser_direction or 'none'
+                choices=roop.choices.face_analyser_direction,
+                value=roop.globals.face_analyser_direction
             )
             FACE_ANALYSER_AGE_DROPDOWN = gradio.Dropdown(
                 label='FACE ANALYSER AGE',
-                choices=['none', 'child', 'teen', 'adult', 'senior'],
+                choices=['none'] + roop.choices.face_analyser_age,
                 value=roop.globals.face_analyser_age or 'none'
             )
             FACE_ANALYSER_GENDER_DROPDOWN = gradio.Dropdown(
                 label='FACE ANALYSER GENDER',
-                choices=['none', 'male', 'female'],
+                choices=['none'] + roop.choices.face_analyser_gender,
                 value=roop.globals.face_analyser_gender or 'none'
             )
         ui.register_component('face_analyser_direction_dropdown', FACE_ANALYSER_DIRECTION_DROPDOWN)

roop/uis/__components__/face_selector.py

@@ -4,6 +4,7 @@
 import cv2
 import gradio
 
+import roop.choices
 import roop.globals
 from roop.capturer import get_video_frame
 from roop.face_analyser import get_many_faces
@@ -40,7 +41,7 @@ def render() -> None:
             reference_face_gallery_args['value'] = extract_gallery_frames(reference_frame)
         FACE_RECOGNITION_DROPDOWN = gradio.Dropdown(
             label='FACE RECOGNITION',
-            choices=['reference', 'many'],
+            choices=roop.choices.face_recognition,
             value=roop.globals.face_recognition
         )
         REFERENCE_FACE_POSITION_GALLERY = gradio.Gallery(**reference_face_gallery_args)

roop/uis/__components__/output_settings.py

@@ -1,9 +1,9 @@
 from typing import Optional
 import gradio
 
+import roop.choices
 import roop.globals
 from roop.typing import OutputVideoEncoder
-
 from roop.uis.typing import Update
 
 OUTPUT_VIDEO_ENCODER_DROPDOWN: Optional[gradio.Dropdown] = None
@@ -17,7 +17,7 @@ def render() -> None:
     with gradio.Box():
         OUTPUT_VIDEO_ENCODER_DROPDOWN = gradio.Dropdown(
             label='OUTPUT VIDEO ENCODER',
-            choices=['libx264', 'libx265', 'libvpx-vp9', 'h264_nvenc', 'hevc_nvenc'],
+            choices=roop.choices.output_video_encoder,
             value=roop.globals.output_video_encoder
         )
         OUTPUT_VIDEO_QUALITY_SLIDER = gradio.Slider(

roop/uis/__components__/temp_frame.py

@@ -1,6 +1,7 @@
 from typing import Optional
 import gradio
 
+import roop.choices
 import roop.globals
 from roop.typing import TempFrameFormat
 
@@ -17,7 +18,7 @@ def render() -> None:
     with gradio.Box():
         TEMP_FRAME_FORMAT_DROPDOWN = gradio.Dropdown(
             label='TEMP FRAME FORMAT',
-            choices=['jpg', 'png'],
+            choices=roop.choices.temp_frame_format,
             value=roop.globals.temp_frame_format
         )
         TEMP_FRAME_QUALITY_SLIDER = gradio.Slider(

roop/uis/core.py

@@ -19,7 +19,7 @@
 
 
 def init() -> None:
-    with gradio.Blocks(theme=get_theme(), title=roop.metadata.name + ' ' + roop.metadata.version) as ui:
+    with gradio.Blocks(theme=get_theme(), title=f'{roop.metadata.name} {roop.metadata.version}') as ui:
         for ui_layout in roop.globals.ui_layouts:
             ui_layout_module = load_ui_layout_module(ui_layout)
             ui_layout_module.render()
@@ -34,7 +34,7 @@ def load_ui_layout_module(ui_layout: str) -> Any:
             if not hasattr(ui_layout_module, method_name):
                 raise NotImplementedError
     except ModuleNotFoundError:
-        sys.exit(f'UI layout {ui_layout} could be not loaded.')
+        sys.exit(f'UI layout {ui_layout} could not be loaded.')
     except NotImplementedError:
         sys.exit(f'UI layout {ui_layout} not implemented correctly.')
     return ui_layout_module