Upload 3 files

app.py

@@ -1,62 +1,45 @@
 import os
-import time
-import shutil
-import pandas as pd
 import gradio as gr
-from vidfetch import youtube_dl_install_helper, push_to_hf
-from panda70m_downloader import download_video_links, download_videos_by_csv
+from openvideo import push_file_to_hf
+try:
+    import ml4co_kit
+except:
+    os.system("pip install ml4co-kit-0.0.2a1.tar.gz")    
+    import ml4co_kit
+from ml4co_kit import CVRPPyVRPSolver
+from ml4co_kit import CVRPDataGenerator
 
-
-SAVE_CSV_DIR = "panda70m_csv"
-SAVE_VIDEOS_DIR = "panda70m_videos"
+FILEPATH = "data/cvrp/uniform/cvrp50_uniform.txt"
 
 def handle(
     hf_token: str, 
     filename: str, 
 ):
-    try:
-        import youtube_dl
-    except:
-        youtube_dl_install_helper(hf_token=hf_token)
-        import youtube_dl
+    solver = CVRPPyVRPSolver(time_limit=10)
+    gen = CVRPDataGenerator(
+        num_threads=8,
+        solver=solver,
+        train_samples_num=6400,
+        val_samples_num=0,
+        test_samples_num=0,
+    )
+    gen.generate()
+    push_file_to_hf(
+        hf_token=hf_token,
+        hf_repo_id="ML4CO/ML4VRP",
+        file_path=FILEPATH,
+        path_in_repo=filename
+    )
     
-    download_video_links(hf_token=hf_token, filename=filename, save_dir=SAVE_CSV_DIR)
     
-    # devide .csv to 100 files and download
-    csv_path = os.path.join(SAVE_CSV_DIR, filename)
-    data = pd.read_csv(csv_path)
-    for idx in range(len(data) // 100):
-        if idx <= 27:
-            continue;
-        begin_idx = idx * 100
-        end_idx = idx * 100 + 100
-        part_data = data[begin_idx : end_idx]
-        part_filename = filename.replace(".csv", "") + "_{:06d}_{:06d}.csv".format(begin_idx, end_idx)
-        targz_filename = part_filename.replace(".csv", ".tar.gz")
-        part_save_path = os.path.join(SAVE_CSV_DIR, part_filename)
-        part_data.to_csv(part_save_path)
-        download_videos_by_csv(
-            csv_file_path=part_save_path,
-            save_dir=SAVE_VIDEOS_DIR,
-            targz_filename=targz_filename
-        )
-        push_to_hf(
-            hf_token=hf_token,
-            hf_repo_id="OpenVideo/Panda-70M-raw",
-            file_path=os.path.join(SAVE_VIDEOS_DIR, targz_filename),
-            path_in_repo=targz_filename
-        )
-        shutil.rmtree(SAVE_VIDEOS_DIR)
-        
-
 with gr.Blocks() as demo:
     gr.Markdown(
         '''
-        Panda70M-Downloader
+        VRP Data Generating
         '''
     )
     hf_token = gr.Textbox(label="HuggingFace Token")
-    filename = gr.Textbox(label="csv name")
+    filename = gr.Textbox(label="txt name")
 
     with gr.Row():
         button = gr.Button("Submit", variant="primary")

requirements.txt

@@ -1,4 +1,4 @@
-vidfetch
+openvideo
 gradio
-pandas
-ml4co-kit
+cython
+pyvrp==0.6.3