Update app.py

app.py

@@ -1,5 +1,6 @@
 import gradio as gr
 import torch.cuda
+from huggingface_hub import hf_hub_download
 
 from InferenceInterfaces.ControllableInterface import ControllableInterface
 from Utility.utils import float2pcm
@@ -8,13 +9,31 @@ from Utility.utils import load_json_from_path
 
 class TTSWebUI:
 
-    def __init__(self, gpu_id="cpu", title="ToucanTTS in 7000 Languages", article="Check out the toolkit at https://github.com/DigitalPhonetics/IMS-Toucan", available_artificial_voices=1000, path_to_iso_list="Preprocessing/multilinguality/iso_to_fullname.json"):
+    def __init__(self,
+                 gpu_id="cpu",
+                 title="Controllable Text-to-Speech for over 7000 Languages",
+                 article="",
+                 tts_model_path=None,
+                 vocoder_model_path=None,
+                 embedding_gan_path=None,
+                 available_artificial_voices=50  # be careful with this, if you want too many, it might lead to an endless loop
+                 ):
+        path_to_iso_list = hf_hub_download(repo_id="Flux9665/ToucanTTS", filename="iso_to_fullname.json")
         iso_to_name = load_json_from_path(path_to_iso_list)
         text_selection = [f"{iso_to_name[iso_code]} ({iso_code})" for iso_code in iso_to_name]
         # accent_selection = [f"{iso_to_name[iso_code]} Accent ({iso_code})" for iso_code in iso_to_name]
+        if tts_model_path is None:
+            tts_model_path = hf_hub_download(repo_id="Flux9665/ToucanTTS", filename="ToucanTTS.pt")
+        if vocoder_model_path is None:
+            vocoder_model_path = hf_hub_download(repo_id="Flux9665/ToucanTTS", filename="Vocoder.pt")
+        if embedding_gan_path is None:
+            embedding_gan_path = hf_hub_download(repo_id="Flux9665/ToucanTTS", filename="embedding_gan.pt")
 
         self.controllable_ui = ControllableInterface(gpu_id=gpu_id,
-                                                     available_artificial_voices=available_artificial_voices)
+                                                     available_artificial_voices=available_artificial_voices,
+                                                     tts_model_path=tts_model_path,
+                                                     vocoder_model_path=vocoder_model_path,
+                                                     embedding_gan_path=embedding_gan_path)
         self.iface = gr.Interface(fn=self.read,
                                   inputs=[gr.Textbox(lines=2,
                                                      placeholder="write what you want the synthesis to read here...",
@@ -24,16 +43,14 @@ class TTSWebUI:
                                                       type="value",
                                                       value='English (eng)',
                                                       label="Select the Language of the Text (type on your keyboard to find it quickly)"),
-                                          gr.Audio(type="filepath", show_label=True, container=True, label="Voice to Clone (if left empty, will use an artificial voice instead)"),
-                                          gr.Slider(minimum=0, maximum=available_artificial_voices, step=1,
-                                                    value=279,
-                                                    label="Random Seed for the artificial Voice"),
-                                          gr.Slider(minimum=0.0, maximum=0.8, step=0.1, value=0.1, label="Prosody Creativity"),
-                                          gr.Slider(minimum=0.7, maximum=1.3, step=0.1, value=1.0, label="Duration Scale"),
+                                          gr.Slider(minimum=0.0, maximum=0.8, step=0.1, value=0.5, label="Prosody Creativity"),
+                                          gr.Slider(minimum=0.7, maximum=1.3, step=0.1, value=1.0, label="Faster - Slower"),
+                                          gr.Slider(minimum=0, maximum=available_artificial_voices, step=1, value=27, label="Random Seed for the artificial Voice"),
+                                          gr.Slider(minimum=-10.0, maximum=10.0, step=0.1, value=0.0, label="Gender of artificial Voice"),
+                                          gr.Audio(type="filepath", show_label=True, container=True, label="[OPTIONAL] Voice to Clone (if left empty, will use an artificial voice instead)"),
                                           # gr.Slider(minimum=0.5, maximum=1.5, step=0.1, value=1.0, label="Pitch Variance Scale"),
                                           # gr.Slider(minimum=0.5, maximum=1.5, step=0.1, value=1.0, label="Energy Variance Scale"),
-                                          gr.Slider(minimum=-10.0, maximum=10.0, step=0.1, value=0.0, label="Femininity / Masculinity"),
-                                          gr.Slider(minimum=-10.0, maximum=10.0, step=0.1, value=0.0, label="Voice Depth")
+                                          # gr.Slider(minimum=-10.0, maximum=10.0, step=0.1, value=0.0, label="Voice Depth")
                                           ],
                                   outputs=[gr.Audio(type="numpy", label="Speech"),
                                            gr.Image(label="Visualization")],
@@ -46,14 +63,14 @@ class TTSWebUI:
     def read(self,
              prompt,
              language,
-             reference_audio,
-             voice_seed,
              prosody_creativity,
              duration_scaling_factor,
+             voice_seed,
+             emb1,
+             reference_audio,
              # pitch_variance_scale,
              # energy_variance_scale,
-             emb1,
-             emb2
+             # emb2
              ):
         sr, wav, fig = self.controllable_ui.read(prompt,
                                                  reference_audio,
@@ -66,12 +83,12 @@ class TTSWebUI:
                                                  1.0,
                                                  1.0,
                                                  emb1,
-                                                 emb2,
                                                  0.,
                                                  0.,
                                                  0.,
                                                  0.,
-                                                 -18.)
+                                                 0.,
+                                                 -12.)
         return (sr, float2pcm(wav)), fig