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__all__ = ['block', 'make_clickable_model', 'make_clickable_user', 'get_submissions']
import os
import io
import gradio as gr
import pandas as pd
import json
import shutil
import tempfile
import datetime
import zipfile
import numpy as np
from constants import *
from huggingface_hub import Repository
HF_TOKEN = os.environ.get("HF_TOKEN")
global data_component, filter_component
def upload_file(files):
file_paths = [file.name for file in files]
return file_paths
# def add_new_eval(
# input_file,
# model_name_textbox: str,
# revision_name_textbox: str,
# model_link: str,
# team_name: str,
# contact_email: str,
# access_type: str,
# model_publish: str,
# model_resolution: str,
# model_fps: str,
# model_frame: str,
# model_video_length: str,
# model_checkpoint: str,
# model_commit_id: str,
# model_video_format: str
# ):
# if input_file is None:
# return "Error! Empty file!"
# if model_link == '' or model_name_textbox == '' or contact_email == '':
# return gr.update(visible=True), gr.update(visible=False), gr.update(visible=True)
# # upload_data=json.loads(input_file)
# upload_content = input_file
# submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset")
# submission_repo.git_pull()
# filename = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
# now = datetime.datetime.now()
# update_time = now.strftime("%Y-%m-%d") # Capture update time
# with open(f'{SUBMISSION_NAME}/{filename}.zip','wb') as f:
# f.write(input_file)
# # shutil.copyfile(CSV_DIR, os.path.join(SUBMISSION_NAME, f"{input_file}"))
# csv_data = pd.read_csv(CSV_DIR)
# if revision_name_textbox == '':
# col = csv_data.shape[0]
# model_name = model_name_textbox.replace(',',' ')
# else:
# model_name = revision_name_textbox.replace(',',' ')
# model_name_list = csv_data['Model Name (clickable)']
# name_list = [name.split(']')[0][1:] for name in model_name_list]
# if revision_name_textbox not in name_list:
# col = csv_data.shape[0]
# else:
# col = name_list.index(revision_name_textbox)
# if model_link == '':
# model_name = model_name # no url
# else:
# model_name = '[' + model_name + '](' + model_link + ')'
# os.makedirs(filename, exist_ok=True)
# with zipfile.ZipFile(io.BytesIO(input_file), 'r') as zip_ref:
# zip_ref.extractall(filename)
# upload_data = {}
# for file in os.listdir(filename):
# if file.startswith('.') or file.startswith('__'):
# print(f"Skip the file: {file}")
# continue
# cur_file = os.path.join(filename, file)
# if os.path.isdir(cur_file):
# for subfile in os.listdir(cur_file):
# if subfile.endswith(".json"):
# with open(os.path.join(cur_file, subfile)) as ff:
# cur_json = json.load(ff)
# print(file, type(cur_json))
# if isinstance(cur_json, dict):
# print(cur_json.keys())
# for key in cur_json:
# upload_data[key.replace('_',' ')] = cur_json[key][0]
# print(f"{key}:{cur_json[key][0]}")
# elif cur_file.endswith('json'):
# with open(cur_file) as ff:
# cur_json = json.load(ff)
# print(file, type(cur_json))
# if isinstance(cur_json, dict):
# print(cur_json.keys())
# for key in cur_json:
# upload_data[key.replace('_',' ')] = cur_json[key][0]
# print(f"{key}:{cur_json[key][0]}")
# # add new data
# new_data = [model_name]
# print('upload_data:', upload_data)
# for key in TASK_INFO:
# if key in upload_data:
# new_data.append(upload_data[key])
# else:
# new_data.append(0)
# if team_name =='' or 'vbench' in team_name.lower():
# new_data.append("User Upload")
# else:
# new_data.append(team_name)
# new_data.append(contact_email.replace(',',' and ')) # Add contact email [private]
# new_data.append(update_time) # Add the update time
# new_data.append(team_name)
# new_data.append(access_type)
# csv_data.loc[col] = new_data
# csv_data = csv_data.to_csv(CSV_DIR, index=False)
# with open(INFO_DIR,'a') as f:
# f.write(f"{model_name}\t{update_time}\t{model_publish}\t{model_resolution}\t{model_fps}\t{model_frame}\t{model_video_length}\t{model_checkpoint}\t{model_commit_id}\t{model_video_format}\n")
# submission_repo.push_to_hub()
# print("success update", model_name)
# return gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)
# def add_new_eval_i2v(
# input_file,
# model_name_textbox: str,
# revision_name_textbox: str,
# model_link: str,
# team_name: str,
# contact_email: str,
# access_type: str,
# model_publish: str,
# model_resolution: str,
# model_fps: str,
# model_frame: str,
# model_video_length: str,
# model_checkpoint: str,
# model_commit_id: str,
# model_video_format: str
# ):
# COLNAME2KEY={
# "Video-Text Camera Motion":"camera_motion",
# "Video-Image Subject Consistency": "i2v_subject",
# "Video-Image Background Consistency": "i2v_background",
# "Subject Consistency": "subject_consistency",
# "Background Consistency": "background_consistency",
# "Motion Smoothness": "motion_smoothness",
# "Dynamic Degree": "dynamic_degree",
# "Aesthetic Quality": "aesthetic_quality",
# "Imaging Quality": "imaging_quality",
# "Temporal Flickering": "temporal_flickering"
# }
# if input_file is None:
# return "Error! Empty file!"
# if model_link == '' or model_name_textbox == '' or contact_email == '':
# return gr.update(visible=True), gr.update(visible=False), gr.update(visible=True)
# upload_content = input_file
# submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset")
# submission_repo.git_pull()
# filename = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
# now = datetime.datetime.now()
# update_time = now.strftime("%Y-%m-%d") # Capture update time
# with open(f'{SUBMISSION_NAME}/{filename}.zip','wb') as f:
# f.write(input_file)
# # shutil.copyfile(CSV_DIR, os.path.join(SUBMISSION_NAME, f"{input_file}"))
# csv_data = pd.read_csv(I2V_DIR)
# if revision_name_textbox == '':
# col = csv_data.shape[0]
# model_name = model_name_textbox.replace(',',' ')
# else:
# model_name = revision_name_textbox.replace(',',' ')
# model_name_list = csv_data['Model Name (clickable)']
# name_list = [name.split(']')[0][1:] for name in model_name_list]
# if revision_name_textbox not in name_list:
# col = csv_data.shape[0]
# else:
# col = name_list.index(revision_name_textbox)
# if model_link == '':
# model_name = model_name # no url
# else:
# model_name = '[' + model_name + '](' + model_link + ')'
# os.makedirs(filename, exist_ok=True)
# with zipfile.ZipFile(io.BytesIO(input_file), 'r') as zip_ref:
# zip_ref.extractall(filename)
# upload_data = {}
# for file in os.listdir(filename):
# if file.startswith('.') or file.startswith('__'):
# print(f"Skip the file: {file}")
# continue
# cur_file = os.path.join(filename, file)
# if os.path.isdir(cur_file):
# for subfile in os.listdir(cur_file):
# if subfile.endswith(".json"):
# with open(os.path.join(cur_file, subfile)) as ff:
# cur_json = json.load(ff)
# print(file, type(cur_json))
# if isinstance(cur_json, dict):
# print(cur_json.keys())
# for key in cur_json:
# upload_data[key] = cur_json[key][0]
# print(f"{key}:{cur_json[key][0]}")
# elif cur_file.endswith('json'):
# with open(cur_file) as ff:
# cur_json = json.load(ff)
# print(file, type(cur_json))
# if isinstance(cur_json, dict):
# print(cur_json.keys())
# for key in cur_json:
# upload_data[key] = cur_json[key][0]
# print(f"{key}:{cur_json[key][0]}")
# # add new data
# new_data = [model_name]
# print('upload_data:', upload_data)
# I2V_HEAD= ["Video-Text Camera Motion",
# "Video-Image Subject Consistency",
# "Video-Image Background Consistency",
# "Subject Consistency",
# "Background Consistency",
# "Temporal Flickering",
# "Motion Smoothness",
# "Dynamic Degree",
# "Aesthetic Quality",
# "Imaging Quality" ]
# for key in I2V_HEAD :
# sub_key = COLNAME2KEY[key]
# if sub_key in upload_data:
# new_data.append(upload_data[sub_key])
# else:
# new_data.append(0)
# if team_name =='' or 'vbench' in team_name.lower():
# new_data.append("User Upload")
# else:
# new_data.append(team_name)
# new_data.append(contact_email.replace(',',' and ')) # Add contact email [private]
# new_data.append(update_time) # Add the update time
# new_data.append(team_name)
# new_data.append(access_type)
# csv_data.loc[col] = new_data
# csv_data = csv_data.to_csv(I2V_DIR , index=False)
# with open(INFO_DIR,'a') as f:
# f.write(f"{model_name}\t{update_time}\t{model_publish}\t{model_resolution}\t{model_fps}\t{model_frame}\t{model_video_length}\t{model_checkpoint}\t{model_commit_id}\t{model_video_format}\n")
# submission_repo.push_to_hub()
# print("success update", model_name)
# return gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)
def get_baseline_df():
submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset")
submission_repo.git_pull()
df = pd.read_csv(CSV_DIR)
df = df.sort_values(by=DEFAULT_INFO[0], ascending=False)
# Add this line to display the results of all model types by default
df = df[df['Model Type'].isin(model_type_filter.value)]
# Add this line to display the results of both abilities by default
df = df[df['Ability'].isin(ability_filter.value)]
return df
def get_all_df(dir=CSV_DIR):
submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset")
submission_repo.git_pull()
df = pd.read_csv(dir)
return df
block = gr.Blocks()
with block:
gr.Markdown(
LEADERBORAD_INTRODUCTION
)
with gr.Tabs(elem_classes="tab-buttons") as tabs:
# Table 0
with gr.TabItem("🏅 WorldScore Benchmark", elem_id="worldscore-tab-table", id=1):
with gr.Column():
model_type_filter = gr.CheckboxGroup(
choices=MODEL_TYPE,
value=DEFAULT_MODEL_TYPE,
label="Model Type",
interactive=True
)
ability_filter = gr.CheckboxGroup(
choices=ABILITY,
value=DEFAULT_ABILITY,
label="Ability",
interactive=True
)
data_component = gr.components.Dataframe(
column_widths="auto", # Automatically adjusts column widths
value=get_baseline_df(),
headers=COLUMN_NAMES,
type="pandas",
datatype=DATA_TITILE_TYPE,
interactive=False,
visible=True,
)
def on_filter_change(model_types, abilities):
df = get_baseline_df()
# Filter by selected model types
df = df[df['Model Type'].isin(model_types)]
# Filter by selected abilities
df = df[df['Ability'].isin(abilities)]
return gr.Dataframe(
column_widths="auto", # Automatically adjusts column widths
value=df,
headers=COLUMN_NAMES,
type="pandas",
datatype=DATA_TITILE_TYPE,
interactive=False,
visible=True
)
model_type_filter.change(
fn=on_filter_change,
inputs=[model_type_filter, ability_filter],
outputs=data_component
)
ability_filter.change(
fn=on_filter_change,
inputs=[model_type_filter, ability_filter],
outputs=data_component
)
# with gr.TabItem("🚀 [I2V]Submit here! ", elem_id="mvbench-i2v-tab-table", id=7):
# gr.Markdown(LEADERBORAD_INTRODUCTION, elem_classes="markdown-text")
# with gr.Row():
# gr.Markdown(SUBMIT_INTRODUCTION, elem_classes="markdown-text")
# with gr.Row():
# gr.Markdown("# ✉️✨ Submit your i2v model evaluation json file here!", elem_classes="markdown-text")
# with gr.Row():
# gr.Markdown("Here is a required field", elem_classes="markdown-text")
# with gr.Row():
# with gr.Column():
# model_name_textbox_i2v = gr.Textbox(
# label="Model name", placeholder="Required field"
# )
# revision_name_textbox_i2v = gr.Textbox(
# label="Revision Model Name(Optional)", placeholder="If you need to update the previous results, please fill in this line"
# )
# access_type_i2v = gr.Dropdown(["Open Source", "Ready to Open Source", "API", "Close"], label="Please select the way user can access your model. You can update the content by revision_name, or contact the VBench Team.")
# with gr.Column():
# model_link_i2v = gr.Textbox(
# label="Project Page/Paper Link/Github/HuggingFace Repo", placeholder="Required field. If filling in the wrong information, your results may be removed."
# )
# team_name_i2v = gr.Textbox(
# label="Your Team Name(If left blank, it will be user upload)", placeholder="User Upload"
# )
# contact_email_i2v = gr.Textbox(
# label="E-Mail(Will not be displayed)", placeholder="Required field"
# )
# with gr.Row():
# gr.Markdown("The following is optional and will be synced to [GitHub] (https://github.com/Vchitect/VBench/tree/master/sampled_videos#what-are-the-details-of-the-video-generation-models)", elem_classes="markdown-text")
# with gr.Row():
# release_time_i2v = gr.Textbox(label="Time of Publish", placeholder="1970-01-01")
# model_resolution_i2v = gr.Textbox(label="resolution", placeholder="Width x Height")
# model_fps_i2v = gr.Textbox(label="model fps", placeholder="FPS(int)")
# model_frame_i2v = gr.Textbox(label="model frame count", placeholder="INT")
# model_video_length_i2v = gr.Textbox(label="model video length", placeholder="float(2.0)")
# model_checkpoint_i2v = gr.Textbox(label="model checkpoint", placeholder="optional")
# model_commit_id_i2v = gr.Textbox(label="github commit id", placeholder='main')
# model_video_format_i2v = gr.Textbox(label="pipeline format", placeholder='mp4')
# with gr.Column():
# input_file_i2v = gr.components.File(label = "Click to Upload a ZIP File", file_count="single", type='binary')
# submit_button_i2v = gr.Button("Submit Eval")
# submit_succ_button_i2v = gr.Markdown("Submit Success! Please press refresh and retfurn to LeaderBoard!", visible=False)
# fail_textbox_i2v = gr.Markdown('<span style="color:red;">Please ensure that the `Model Name`, `Project Page`, and `Email` are filled in correctly.</span>', elem_classes="markdown-text",visible=False)
# submission_result_i2v = gr.Markdown()
# # submit_button_i2v.click(
# # add_new_eval_i2v,
# # inputs = [
# # input_file_i2v,
# # model_name_textbox_i2v,
# # revision_name_textbox_i2v,
# # model_link_i2v,
# # team_name_i2v,
# # contact_email_i2v,
# # release_time_i2v,
# # access_type_i2v,
# # model_resolution_i2v,
# # model_fps_i2v,
# # model_frame_i2v,
# # model_video_length_i2v,
# # model_checkpoint_i2v,
# # model_commit_id_i2v,
# # model_video_format_i2v
# # ],
# # outputs=[submit_button_i2v, submit_succ_button_i2v, fail_textbox_i2v]
# # )
# def refresh_data():
# value1 = get_baseline_df()
# return value1
# with gr.Row():
# data_run = gr.Button("Refresh")
# data_run.click(on_filter_model_size_method_change, inputs=[checkbox_group], outputs=data_component)
block.launch()
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