Update app.py

app.py

@@ -10,38 +10,102 @@ import traceback
 from pydub import AudioSegment
 # from audio_enhance.functions import audio_enhance
 
-def convert_yt_to_wav(url):
-    if not url:
-        return "Primero introduce el enlace del video", None
-    
-    try:
-        print(f"Convirtiendo video {url}...")
-        # Descargar el video utilizando pytube
-        video = pytube.YouTube(url)
-        stream = video.streams.filter(only_audio=True).first()
-        video_output_folder = os.path.join(f"yt_videos")  # Ruta de destino de la carpeta
-        audio_output_folder = 'audios'
-
-        print("Downloading video")
-        video_file_path = stream.download(output_path=video_output_folder)
-        print(video_file_path)
-
-        file_name = os.path.basename(video_file_path)
-        
-        audio_file_path = os.path.join(audio_output_folder, file_name.replace('.mp4','.wav'))
-        # convert mp4 to wav
-        print("Converting to wav")
-        sound = AudioSegment.from_file(video_file_path,format="mp4")
-        sound.export(audio_file_path, format="wav")
-        
-        if os.path.exists(video_file_path):
-            os.remove(video_file_path)
-            
-        return "Success", audio_file_path
-    except ConnectionResetError as cre:
-        return "Se ha perdido la conexión, recarga o reintentalo nuevamente más tarde.", None
-    except Exception as e:
-        return str(e), None
+import ast
+import argparse
+import glob
+import pickle
+
+import numpy as np
+import pandas as pd
+block_css = """
+#notice_markdown {
+    font-size: 104%
+}
+#notice_markdown th {
+    display: none;
+}
+#notice_markdown td {
+    padding-top: 6px;
+    padding-bottom: 6px;
+}
+#leaderboard_markdown {
+    font-size: 104%
+}
+#leaderboard_markdown td {
+    padding-top: 6px;
+    padding-bottom: 6px;
+}
+#leaderboard_dataframe td {
+    line-height: 0.1em;
+}
+footer {
+    display:none !important
+}
+.image-container {
+    display: flex;
+    align-items: center;
+    padding: 1px;
+}
+.image-container img {
+    margin: 0 30px;
+    height: 20px;
+    max-height: 100%;
+    width: auto;
+    max-width: 20%;
+}
+"""
+def model_hyperlink(model_name, link):
+    return f'<a target="_blank" href="{link}" style="color: var(--link-text-color); text-decoration: underline;text-decoration-style: dotted;">{model_name}</a>'
+def load_leaderboard_table_csv(filename, add_hyperlink=True):
+    lines = open(filename).readlines()
+    heads = [v.strip() for v in lines[0].split(",")]
+    rows = []
+    for i in range(1, len(lines)):
+        row = [v.strip() for v in lines[i].split(",")]
+        for j in range(len(heads)):
+            item = {}
+            for h, v in zip(heads, row):
+                if h != "AI歌手名/AI Singer" and h != "歌手代表作或介绍链接" and h != "模型zip链接/Link to Model Zip File" and h != "模型贡献者/Model Contributor":
+                    item[h] = int(v)
+                else:
+                    item[h] = v
+            if add_hyperlink:
+                item["AI歌手名/AI Singer"] = model_hyperlink(item["AI歌手名/AI Singer"], item["歌手代表作或介绍链接"])
+        rows.append(item)
+    return rows
+
+def get_arena_table(model_table_df):
+    # sort by rating
+    model_table_df = model_table_df.sort_values(by=["训练素材时长/Duration of Training Dataset(min)"], ascending=False)
+    values = []
+    for i in range(len(model_table_df)):
+        row = []
+        model_key = model_table_df.index[i]
+        model_name = model_table_df["AI歌手名/AI Singer"].values[model_key]
+        # rank
+        row.append(i + 1)
+        # model display name
+        row.append(model_name)
+
+        row.append(
+            model_table_df["模型zip链接/Link to Model Zip File"].values[model_key]
+        )
+
+        row.append(
+            model_table_df["训练素材时长/Duration of Training Dataset(min)"].values[model_key]
+        )
+
+        row.append(
+            model_table_df["训练epoch数/Epoch"].values[model_key]
+        )
+
+        row.append(
+            model_table_df["模型贡献者/Model Contributor"].values[model_key]
+        )
+
+        values.append(row)
+    return values
+
 
 
 title_markdown = ("""
@@ -54,11 +118,11 @@ pic_markdown = ("""
 <h1 align="center"><a href="https://www.talktalkai.com/"><img src="https://download.openxlab.org.cn/models/Kevin676/rvc-models/weight/talktalkai-cover.png", alt="talktalkai-cover" border="0" style="margin: 0 auto; height: 300px;" /></a> </h1>
 """)
 
-with gr.Blocks() as app:
+with gr.Blocks(theme="JohnSmith9982/small_and_pretty", css=block_css) as app:
     
     gr.Markdown(title_markdown)
 
-    with gr.Tab("模型搜索及上传"):
+    with gr.Tab("✨模型搜索及上传"):
         gr.HTML("<h3>1. 搜索AI歌手模型</h3>")
         gr.Markdown("##### 点击[此链接](https://docs.google.com/spreadsheets/d/1owfUtQuLW9ReiIwg6U9UkkDmPOTkuNHf0OKQtWu1iaI/edit?gid=1227575351#gid=1227575351)，查看全网所有开源AI歌手模型，超9000个模型任您挑选 🥳")
         search_name = gr.Textbox(placeholder="孙燕姿", label="请填写模型名称进行搜索", show_label=True)
@@ -82,7 +146,38 @@ with gr.Blocks() as app:
             
         btn_post_model = gr.Button(value="开始上传吧💕", variant="primary")
         btn_post_model.click(fn=post_model, inputs=[post_name, post_model_url, post_version, post_creator], outputs=[post_output])
-                
+
+    with gr.Tab("🍻滔滔AI精选模型"):
+        arena_table_vals = get_arena_table(model_table_df)
+        md = """
+        AI翻唱🎶：您可以在社区中复制您喜欢的AI歌手的“模型zip链接”，之后就可以在“🌟重磅首发 - AI歌手全明星💕”页面中通过粘贴zip链接来使用您喜欢的AI歌手模型啦！\n
+        [手机端📱](https://kevinwang676-talktalkai-models.hf.space)查看滔滔AI精选模型
+        """
+        gr.Markdown(md, elem_id="leaderboard_markdown")
+        gr.Dataframe(
+            headers=[
+                "排序",
+                "AI歌手名/AI Singer",
+                "模型zip链接/Link to Model Zip File",
+                "训练素材时长/Duration of Training Dataset(min)",
+                "训练epoch数/Epoch",
+                "模型贡献者/Model Contributor",
+            ],
+            datatype=[
+                "str",
+                "markdown",
+                "str",
+                "number",
+                "number",
+                "str",
+            ],
+            value=arena_table_vals,
+            elem_id="arena_leaderboard_dataframe",
+            height=800,
+            column_widths=[50, 100, 205, 95, 95, 95],
+            wrap=True,
+        )
+
     gr.Markdown(pic_markdown)
     gr.Markdown("###### <center>注意❗：请不要生成会对个人以及组织造成侵害的内容，此程序仅供科研、学习及个人娱乐使用。请自觉合规使用此程序，程序开发者不负有任何责任。</center>")