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Update app.py
Browse files
app.py
CHANGED
@@ -125,6 +125,133 @@ def add_new_eval(
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print("success update", model_name)
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return gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)
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def get_normalized_df(df):
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# final_score = df.drop('name', axis=1).sum(axis=1)
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# df.insert(1, 'Overall Score', final_score)
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@@ -137,7 +264,7 @@ def get_normalized_df(df):
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def get_normalized_i2v_df(df):
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normalize_df = df.copy().fillna(0.0)
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-
for column in normalize_df.columns[1
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min_val = NORMALIZE_DIC_I2V[column]['Min']
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max_val = NORMALIZE_DIC_I2V[column]['Max']
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normalize_df[column] = (normalize_df[column] - min_val) / (max_val - min_val)
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@@ -208,7 +335,7 @@ def get_final_score(df, selected_columns):
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def get_final_score_i2v(df, selected_columns):
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normalize_df = get_normalized_i2v_df(df)
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#final_score = normalize_df.drop('name', axis=1).sum(axis=1)
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-
for name in normalize_df.drop('Model Name (clickable)', axis=1).drop('Video-Text Camera Motion', axis=1):
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normalize_df[name] = normalize_df[name]*DIM_WEIGHT_I2V[name]
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quality_score = normalize_df[I2V_QUALITY_LIST].sum(axis=1)/sum([DIM_WEIGHT_I2V[i] for i in I2V_QUALITY_LIST])
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i2v_score = normalize_df[I2V_LIST].sum(axis=1)/sum([DIM_WEIGHT_I2V[i] for i in I2V_LIST ])
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@@ -603,7 +730,7 @@ with block:
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gr.Markdown(LEADERBORAD_INFO, elem_classes="markdown-text")
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# table submission
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with gr.TabItem("π Submit here! ", elem_id="mvbench-tab-table", id=6):
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gr.Markdown(LEADERBORAD_INTRODUCTION, elem_classes="markdown-text")
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with gr.Row():
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@@ -672,6 +799,77 @@ with block:
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],
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outputs=[submit_button, submit_succ_button, fail_textbox]
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)
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def refresh_data():
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print("success update", model_name)
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return gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)
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def add_new_eval_i2v(
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input_file,
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model_name_textbox: str,
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revision_name_textbox: str,
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model_link: str,
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team_name: str,
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contact_email: str,
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model_publish: str,
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model_resolution: str,
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model_fps: str,
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model_frame: str,
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model_video_length: str,
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model_checkpoint: str,
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model_commit_id: str,
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model_video_format: str
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):
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COLNAME2KEY={
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"Video-Text Camera Motion":"camera_motion",
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"Video-Image Subject Consistency": "i2v_subject",
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"Video-Image Background Consistency": "i2v_background",
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"Subject Consistency": "subject_consistency",
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"Background Consistency": "background_consistency",
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"Motion Smoothness": "motion_smoothness",
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"Dynamic Degree": "dynamic_degree",
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"Aesthetic Quality": "aesthetic_quality",
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"Imaging Quality": "imaging_quality",
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"Temporal Flickering": "temporal_flickering"
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}
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if input_file is None:
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return "Error! Empty file!"
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if model_link == '' or model_name_textbox == '' or contact_email == '':
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return gr.update(visible=True), gr.update(visible=False), gr.update(visible=True)
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upload_content = input_file
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submission_repo = Repository(local_dir=SUBMISSION_NAME, clone_from=SUBMISSION_URL, use_auth_token=HF_TOKEN, repo_type="dataset")
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submission_repo.git_pull()
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filename = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
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now = datetime.datetime.now()
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update_time = now.strftime("%Y-%m-%d") # Capture update time
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with open(f'{SUBMISSION_NAME}/{filename}.zip','wb') as f:
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f.write(input_file)
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# shutil.copyfile(CSV_DIR, os.path.join(SUBMISSION_NAME, f"{input_file}"))
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csv_data = pd.read_csv(I2V_DIR)
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if revision_name_textbox == '':
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col = csv_data.shape[0]
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model_name = model_name_textbox.replace(',',' ')
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else:
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model_name = revision_name_textbox.replace(',',' ')
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model_name_list = csv_data['Model Name (clickable)']
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name_list = [name.split(']')[0][1:] for name in model_name_list]
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if revision_name_textbox not in name_list:
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col = csv_data.shape[0]
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else:
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col = name_list.index(revision_name_textbox)
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if model_link == '':
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model_name = model_name # no url
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else:
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model_name = '[' + model_name + '](' + model_link + ')'
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os.makedirs(filename, exist_ok=True)
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with zipfile.ZipFile(io.BytesIO(input_file), 'r') as zip_ref:
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zip_ref.extractall(filename)
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upload_data = {}
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for file in os.listdir(filename):
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if file.startswith('.') or file.startswith('__'):
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print(f"Skip the file: {file}")
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continue
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cur_file = os.path.join(filename, file)
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if os.path.isdir(cur_file):
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for subfile in os.listdir(cur_file):
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if subfile.endswith(".json"):
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with open(os.path.join(cur_file, subfile)) as ff:
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cur_json = json.load(ff)
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print(file, type(cur_json))
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if isinstance(cur_json, dict):
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print(cur_json.keys())
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for key in cur_json:
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upload_data[key] = cur_json[key][0]
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print(f"{key}:{cur_json[key][0]}")
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elif cur_file.endswith('json'):
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with open(cur_file) as ff:
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cur_json = json.load(ff)
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print(file, type(cur_json))
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if isinstance(cur_json, dict):
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print(cur_json.keys())
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for key in cur_json:
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upload_data[key] = cur_json[key][0]
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print(f"{key}:{cur_json[key][0]}")
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# add new data
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new_data = [model_name]
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print('upload_data:', upload_data)
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I2V_HEAD= ["Video-Text Camera Motion",
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"Video-Image Subject Consistency",
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"Video-Image Background Consistency",
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"Subject Consistency",
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"Background Consistency",
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"Temporal Flickering",
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"Motion Smoothness",
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"Dynamic Degree",
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"Aesthetic Quality",
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"Imaging Quality" ]
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for key in I2V_HEAD :
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sub_key = COLNAME2KEY[key]
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if sub_key in upload_data:
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new_data.append(upload_data[sub_key])
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else:
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new_data.append(0)
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if team_name =='' or 'vbench' in team_name.lower():
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new_data.append("User Upload")
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else:
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new_data.append(team_name)
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new_data.append(contact_email.replace(',',' and ')) # Add contact email [private]
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new_data.append(update_time) # Add the update time
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csv_data.loc[col] = new_data
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csv_data = csv_data.to_csv(I2V_DIR , index=False)
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with open(INFO_DIR,'a') as f:
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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")
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submission_repo.push_to_hub()
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print("success update", model_name)
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return gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)
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def get_normalized_df(df):
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# final_score = df.drop('name', axis=1).sum(axis=1)
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# df.insert(1, 'Overall Score', final_score)
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def get_normalized_i2v_df(df):
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normalize_df = df.copy().fillna(0.0)
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for column in normalize_df.columns[1:-3]:
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min_val = NORMALIZE_DIC_I2V[column]['Min']
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max_val = NORMALIZE_DIC_I2V[column]['Max']
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normalize_df[column] = (normalize_df[column] - min_val) / (max_val - min_val)
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def get_final_score_i2v(df, selected_columns):
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normalize_df = get_normalized_i2v_df(df)
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#final_score = normalize_df.drop('name', axis=1).sum(axis=1)
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for name in normalize_df.drop('Model Name (clickable)', axis=1).drop('Video-Text Camera Motion', axis=1).drop('Source', axis=1).drop('Mail', axis=1).drop('Date',axis=1):
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normalize_df[name] = normalize_df[name]*DIM_WEIGHT_I2V[name]
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quality_score = normalize_df[I2V_QUALITY_LIST].sum(axis=1)/sum([DIM_WEIGHT_I2V[i] for i in I2V_QUALITY_LIST])
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i2v_score = normalize_df[I2V_LIST].sum(axis=1)/sum([DIM_WEIGHT_I2V[i] for i in I2V_LIST ])
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gr.Markdown(LEADERBORAD_INFO, elem_classes="markdown-text")
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# table submission
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with gr.TabItem("π [T2V]Submit here! ", elem_id="mvbench-tab-table", id=6):
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gr.Markdown(LEADERBORAD_INTRODUCTION, elem_classes="markdown-text")
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with gr.Row():
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],
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outputs=[submit_button, submit_succ_button, fail_textbox]
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)
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with gr.TabItem("π [I2V]Submit here! ", elem_id="mvbench-i2v-tab-table", id=7):
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gr.Markdown(LEADERBORAD_INTRODUCTION, elem_classes="markdown-text")
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with gr.Row():
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gr.Markdown(SUBMIT_INTRODUCTION, elem_classes="markdown-text")
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with gr.Row():
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gr.Markdown("# βοΈβ¨ Submit your i2v model evaluation json file here!", elem_classes="markdown-text")
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with gr.Row():
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gr.Markdown("Here is a required field", elem_classes="markdown-text")
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with gr.Row():
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with gr.Column():
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model_name_textbox_i2v = gr.Textbox(
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label="Model name", placeholder="Required field"
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)
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revision_name_textbox_i2v = gr.Textbox(
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label="Revision Model Name(Optional)", placeholder="If you need to update the previous results, please fill in this line"
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)
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with gr.Column():
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model_link_i2v = gr.Textbox(
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label="Project Page/Paper Link/Github/HuggingFace Repo", placeholder="Required field. If filling in the wrong information, your results may be removed."
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)
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team_name_i2v = gr.Textbox(
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label="Your Team Name(If left blank, it will be user upload)", placeholder="User Upload"
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)
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contact_email_i2v = gr.Textbox(
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label="E-Mail(Will not be displayed)", placeholder="Required field"
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)
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with gr.Row():
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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")
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with gr.Row():
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release_time_i2v = gr.Textbox(label="Time of Publish", placeholder="1970-01-01")
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model_resolution_i2v = gr.Textbox(label="resolution", placeholder="Width x Height")
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model_fps_i2v = gr.Textbox(label="model fps", placeholder="FPS(int)")
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model_frame_i2v = gr.Textbox(label="model frame count", placeholder="INT")
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model_video_length_i2v = gr.Textbox(label="model video length", placeholder="float(2.0)")
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model_checkpoint_i2v = gr.Textbox(label="model checkpoint", placeholder="optional")
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model_commit_id_i2v = gr.Textbox(label="github commit id", placeholder='main')
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model_video_format_i2v = gr.Textbox(label="pipeline format", placeholder='mp4')
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with gr.Column():
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input_file_i2v = gr.components.File(label = "Click to Upload a ZIP File", file_count="single", type='binary')
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submit_button_i2v = gr.Button("Submit Eval")
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submit_succ_button_i2v = gr.Markdown("Submit Success! Please press refresh and return to LeaderBoard!", visible=False)
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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)
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submission_result_i2v = gr.Markdown()
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submit_button_i2v.click(
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add_new_eval_i2v,
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inputs = [
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input_file_i2v,
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model_name_textbox_i2v,
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revision_name_textbox_i2v,
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model_link_i2v,
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team_name_i2v,
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contact_email_i2v,
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release_time_i2v,
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model_resolution_i2v,
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model_fps_i2v,
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model_frame_i2v,
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model_video_length_i2v,
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model_checkpoint_i2v,
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model_commit_id_i2v,
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model_video_format_i2v
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],
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outputs=[submit_button_i2v, submit_succ_button_i2v, fail_textbox_i2v]
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)
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def refresh_data():
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