Update app.py

app.py

@@ -166,7 +166,7 @@ def get_huggingface_dataset():
     log_file = os.path.join(dataset_dir, "flag_data.csv")
     return repo, log_file
 
-def update(user_choice, left, right, choose_env, data_folder=VIDEO_PATH, flag_to_huggingface=False):
+def update(user_choice, user_name, left, right, choose_env, data_folder=VIDEO_PATH, flag_to_huggingface=False):
     global last_left_video_path 
     global last_right_video_path 
     global last_infer_left_video_path
@@ -175,7 +175,7 @@ def update(user_choice, left, right, choose_env, data_folder=VIDEO_PATH, flag_to
     if flag_to_huggingface: # log
         env_name = str(last_left_video_path).split('/')[1]  # 'robotinder-data/ENV_NAME/'
         current_time = strftime("%Y-%m-%d-%H-%M-%S", gmtime())
-        info = [env_name, user_choice, last_left_video_path, last_right_video_path, current_time]
+        info = [env_name, user_choice, last_left_video_path, last_right_video_path, current_time, user_name]
         print(info)
         repo, log_file = get_huggingface_dataset()
         with open(log_file, 'a') as file: # incremental change of the file
@@ -327,6 +327,7 @@ def build_interface(iter=3, data_folder=VIDEO_PATH):
         last_infer_right_video_path = infer_right_video_path
 
         # btn1 = gr.Button("Replay")
+        user_name = gr.Textbox(label='Your name/email:')
         user_choice = gr.Radio(["Left", "Right", "Not Sure", "Both Good", "Both Bad"], label="Which one is your favorite?")
         choose_env = gr.Radio(["Random"]+ENVS, label="Choose the next task:")
         btn2 = gr.Button("Next")
@@ -335,7 +336,7 @@ def build_interface(iter=3, data_folder=VIDEO_PATH):
         # callback.setup([user_choice, left, right], "flagged_data_points")
         
         # btn1.click(fn=replay, inputs=[left, right], outputs=[left, right])
-        btn2.click(fn=update, inputs=[user_choice, left, right, choose_env], outputs=[left, right, str_env_name])
+        btn2.click(fn=update, inputs=[user_choice, user_name, left, right, choose_env], outputs=[left, right, str_env_name])
 
         # We can choose which components to flag -- in this case, we'll flag all of them
         # btn2.click(lambda *args: callback.flag(args), [user_choice, left, right], None, preprocess=False)  # not using the gradio flagging anymore