Update full_inference.py

Author: TheNeodev

tabs/full_inference.py

@@ -1,6 +1,282 @@
-from tabs.settinginf import *
-
+from core import full_inference_program, download_music
+import sys, os
+import gradio as gr
+import regex as re
+from assets.i18n.i18n import I18nAuto
+import torch
+import shutil
+import unicodedata
 import gradio as gr
+from assets.i18n.i18n import I18nAuto
+
+
+i18n = I18nAuto()
+
+
+now_dir = os.getcwd()
+sys.path.append(now_dir)
+
+
+model_root = os.path.join(now_dir, "logs")
+audio_root = os.path.join(now_dir, "audio_files", "original_files")
+
+
+model_root_relative = os.path.relpath(model_root, now_dir)
+audio_root_relative = os.path.relpath(audio_root, now_dir)
+
+
+sup_audioext = {
+    "wav",
+    "mp3",
+    "flac",
+    "ogg",
+    "opus",
+    "m4a",
+    "mp4",
+    "aac",
+    "alac",
+    "wma",
+    "aiff",
+    "webm",
+    "ac3",
+}
+
+
+names = [
+    os.path.join(root, file)
+    for root, _, files in os.walk(model_root_relative, topdown=False)
+    for file in files
+    if (
+        file.endswith((".pth", ".onnx"))
+        and not (file.startswith("G_") or file.startswith("D_"))
+    )
+]
+
+
+indexes_list = [
+    os.path.join(root, name)
+    for root, _, files in os.walk(model_root_relative, topdown=False)
+    for name in files
+    if name.endswith(".index") and "trained" not in name
+]
+
+
+audio_paths = [
+    os.path.join(root, name)
+    for root, _, files in os.walk(audio_root_relative, topdown=False)
+    for name in files
+    if name.endswith(tuple(sup_audioext))
+    and root == audio_root_relative
+    and "_output" not in name
+]
+
+
+vocals_model_names = [
+    "Mel-Roformer by KimberleyJSN",
+    "BS-Roformer by ViperX",
+    "MDX23C",
+]
+
+
+karaoke_models_names = [
+    "Mel-Roformer Karaoke by aufr33 and viperx",
+    "UVR-BVE",
+]
+
+
+denoise_models_names = [
+    "Mel-Roformer Denoise Normal by aufr33",
+    "Mel-Roformer Denoise Aggressive by aufr33",
+    "UVR Denoise",
+]
+
+
+dereverb_models_names = [
+    "MDX23C DeReverb by aufr33 and jarredou",
+    "UVR-Deecho-Dereverb",
+    "MDX Reverb HQ by FoxJoy",
+    "BS-Roformer Dereverb by anvuew",
+]
+
+
+deeecho_models_names = ["UVR-Deecho-Normal", "UVR-Deecho-Aggressive"]
+
+
+def get_indexes():
+
+    indexes_list = [
+        os.path.join(dirpath, filename)
+        for dirpath, _, filenames in os.walk(model_root_relative)
+        for filename in filenames
+        if filename.endswith(".index") and "trained" not in filename
+    ]
+
+    return indexes_list if indexes_list else ""
+
+
+def match_index(model_file_value):
+    if model_file_value:
+        model_folder = os.path.dirname(model_file_value)
+        model_name = os.path.basename(model_file_value)
+        index_files = get_indexes()
+        pattern = r"^(.*?)_"
+        match = re.match(pattern, model_name)
+        for index_file in index_files:
+            if os.path.dirname(index_file) == model_folder:
+                return index_file
+
+            elif match and match.group(1) in os.path.basename(index_file):
+                return index_file
+
+            elif model_name in os.path.basename(index_file):
+                return index_file
+
+    return ""
+
+
+def output_path_fn(input_audio_path):
+    original_name_without_extension = os.path.basename(input_audio_path).rsplit(".", 1)[
+        0
+    ]
+    new_name = original_name_without_extension + "_output.wav"
+    output_path = os.path.join(os.path.dirname(input_audio_path), new_name)
+
+    return output_path
+
+
+def get_number_of_gpus():
+    if torch.cuda.is_available():
+        num_gpus = torch.cuda.device_count()
+
+        return "-".join(map(str, range(num_gpus)))
+
+    else:
+
+        return "-"
+
+
+def max_vram_gpu(gpu):
+
+    if torch.cuda.is_available():
+        gpu_properties = torch.cuda.get_device_properties(gpu)
+        total_memory_gb = round(gpu_properties.total_memory / 1024 / 1024 / 1024)
+
+        return total_memory_gb / 2
+
+    else:
+
+        return "0"
+
+
+def format_title(title):
+
+    formatted_title = (
+        unicodedata.normalize("NFKD", title).encode("ascii", "ignore").decode("utf-8")
+    )
+
+    formatted_title = re.sub(r"[\u2500-\u257F]+", "", formatted_title)
+    formatted_title = re.sub(r"[^\w\s.-]", "", formatted_title)
+    formatted_title = re.sub(r"\s+", "_", formatted_title)
+
+    return formatted_title
+
+
+def save_to_wav(upload_audio):
+
+    file_path = upload_audio
+    formated_name = format_title(os.path.basename(file_path))
+    target_path = os.path.join(audio_root_relative, formated_name)
+
+    if os.path.exists(target_path):
+        os.remove(target_path)
+
+    os.makedirs(os.path.dirname(target_path), exist_ok=True)
+    shutil.copy(file_path, target_path)
+    
+    return target_path, output_path_fn(target_path)
+
+
+def delete_outputs():
+    gr.Info(f"Outputs cleared!")
+    for root, _, files in os.walk(audio_root_relative, topdown=False):
+        for name in files:
+            if name.endswith(tuple(sup_audioext)) and name.__contains__("_output"):
+                os.remove(os.path.join(root, name))
+
+
+def change_choices():
+    names = [
+        os.path.join(root, file)
+        for root, _, files in os.walk(model_root_relative, topdown=False)
+        for file in files
+        if (
+            file.endswith((".pth", ".onnx"))
+            and not (file.startswith("G_") or file.startswith("D_"))
+        )
+    ]
+
+    indexes_list = [
+        os.path.join(root, name)
+        for root, _, files in os.walk(model_root_relative, topdown=False)
+        for name in files
+        if name.endswith(".index") and "trained" not in name
+    ]
+
+    audio_paths = [
+        os.path.join(root, name)
+        for root, _, files in os.walk(audio_root_relative, topdown=False)
+        for name in files
+        if name.endswith(tuple(sup_audioext))
+        and root == audio_root_relative
+        and "_output" not in name
+    ]
+
+    return (
+        {"choices": sorted(names), "__type__": "update"},
+        {"choices": sorted(indexes_list), "__type__": "update"},
+        {"choices": sorted(audio_paths), "__type__": "update"},
+    )
+
+
+
+
+def update_dropdown_visibility(checkbox):
+
+        return gr.update(visible=checkbox)
+
+    def update_reverb_sliders_visibility(reverb_checked):
+
+        return {
+            reverb_room_size: gr.update(visible=reverb_checked),
+            reverb_damping: gr.update(visible=reverb_checked),
+            reverb_wet_gain: gr.update(visible=reverb_checked),
+            reverb_dry_gain: gr.update(visible=reverb_checked),
+            reverb_width: gr.update(visible=reverb_checked),
+        }
+
+    def update_visibility_infer_backing(infer_backing_vocals):
+
+        visible = infer_backing_vocals
+
+        return (
+            {"visible": visible, "__type__": "update"},
+            {"visible": visible, "__type__": "update"},
+            {"visible": visible, "__type__": "update"},
+            {"visible": visible, "__type__": "update"},
+            {"visible": visible, "__type__": "update"},
+        )
+
+    def update_hop_length_visibility(pitch_extract_value):
+
+        return gr.update(visible=pitch_extract_value in ["crepe", "crepe-tiny"])
+
+
+
+
+
+
+
+