Feat: Allow random IDs

app.py

@@ -34,7 +34,9 @@ with (gr.Blocks(theme=gr.themes.Soft(), css = css) as demo):
     
     # Instructions for emotion annotation
     with gr.Sidebar(open = True) as sidebar:
-        participant_id = gr.Textbox(label='What is your participant ID?', interactive = True)
+        
+        explanation = gr.Textbox(label="What is your participant ID?", interactive=False, value = "Please provide your Participant ID below. If you don't have one, feel free to define your own. Note that it's important to remember your ID so you can return to your annotations.")
+        participant_id = gr.Textbox(label="ID", interactive = True)
         lets_go = gr.Button("Let's go!")
         cheat_sheet = gr.HTML(side_bar_html, padding = False)
         

load_and_save.py

@@ -11,19 +11,17 @@ from text_explanations import *
 from utils import *
 from datetime import datetime
 
-possible_ids = {'Tiger-001': 0, 'Falcon-002': 0, 
-                'Elephant-003': 1, 'Panther-004': 1,
-                'Zebra-005': 2, 'Wolf-006': 2,
-                'Koala-007': 3, 'Otter-008': 3,
-                'Leopard-009': 4, 'Panda-010': 4,
-                'Cheetah-011': 5, 'Gorilla-012': 5,
-                'Dolphin-013' : 6, 'Lynx-014': 6,
-                'Moose-015': 7, 'Raccoon-016': 7,
-                'Rabbit-017': 0, 'Eagle-018': 8, 'Jaguar-019': 8}
+import pickle 
 
 persistent_storage = Path('/data')
 password_files = os.getenv("password_files")
 
+if os.path.exists(f'{persistent_storage}/possible_ids.pkl'):
+    with open(f'{persistent_storage}/possible_ids.pkl', 'wb') as f:
+        possible_ids = pickle.load(f)
+else:
+    possible_ids = {}
+
 def load_first_example(annotations_df, file_list_df, id, completed, index):
     """ Loads and first example and updates index
     
@@ -78,7 +76,7 @@ def load_example(annotations_df, file_list_df, index):
     """
     if index < len(file_list_df):
         row = file_list_df.iloc[index]
-        audio_path = os.path.join(persistent_storage, 'files_to_annotate_2round', row["sample_id"].split('-')[0], row["sample_id"] + '.wav')
+        audio_path = os.path.join(persistent_storage, 'files_to_annotate', row["sample_id"].split('-')[0], row["sample_id"] + '.wav')
         sentence = row["sentence"]
 
         # If the user already made an annotation for this example, gradio will return said annotation
@@ -94,7 +92,7 @@ def load_example(annotations_df, file_list_df, index):
     else:
         index -= 1
         row = file_list_df.iloc[index]
-        audio_path = os.path.join(persistent_storage, 'files_to_annotate_2round', row["sample_id"].split('-')[0], row["sample_id"] + '.wav')
+        audio_path = os.path.join(persistent_storage, 'files_to_annotate', row["sample_id"].split('-')[0], row["sample_id"] + '.wav')
         sentence = row["sentence"]
 
         # If the user already made an annotation for this example, gradio will return said annotation
@@ -236,25 +234,26 @@ def previous_example(annotations_df, file_list_df, emotion, confidence, comments
 def deactivate_participant_id(annotations_df, file_list_df, total, participant_id, lets_go, previous_button, next_button, sentence_text, audio_player, emotions, confidence, comments, n_clicks, ann_completed, current_index):
 
 
-    if participant_id in possible_ids.keys():
-        file_list_df = pd.read_csv(os.path.join(persistent_storage, 'files_to_annotate_2round', f'group_{possible_ids[participant_id]}_v2.csv'), keep_default_na=False)
+    if participant_id not in  possible_ids.keys():
+        possible_ids[participant_id] = 0
+        with open(f'{persistent_storage}/possible_ids.pkl', 'wb') as f:
+            pickle.dump(possible_ids, f)
 
-        total = len(file_list_df)
-    
+    file_list_df = pd.read_csv(os.path.join(persistent_storage, 'files_to_annotate', f'group_{possible_ids[participant_id]}.csv'), keep_default_na=False)
 
-        annotations_df, sentence, audio_player, emotions, confidence, comments, n_clicks, start, end, duration, ann_completed, current_index = load_first_example(annotations_df, file_list_df, participant_id, ann_completed, current_index)
-  
-        participant_id = gr.Textbox(label='What is your participant ID?', value = participant_id, interactive = False)
-        lets_go = gr.Button("Participant selected!", interactive = False)
-        
-        sentence_text = gr.Textbox(label="Transcription", interactive=False, value = sentence)
-        emotions = gr.Radio(["Blank", "Happy", "Sad", "Angry", "Neutral"], label="Predominant Emotion (Check the sidebar for major subclasses)", value =  emotions, visible = True)
-        confidence = gr.Radio(["Blank","Very Uncertain", "Somewhat Uncertain", "Neutral", "Somewhat confident", "Very confident"], label="How confident are you that the annotated emotion is present in the recording?", visible = True, value = confidence)
-        comments = gr.Textbox(label="Comments", visible =True, value = comments)
-        previous_button = gr.Button("Previous Example", visible = True)
-        next_button = gr.Button("Next Example",visible = True)
-        
-        return annotations_df, file_list_df, participant_id, participant_id, lets_go, total, previous_button, next_button, sentence_text, audio_player, emotions, confidence, comments, n_clicks, start, end, duration, ann_completed, current_index
+    total = len(file_list_df)
 
-    else:
-        raise gr.Error("Please insert a valid participant ID")
+
+    annotations_df, sentence, audio_player, emotions, confidence, comments, n_clicks, start, end, duration, ann_completed, current_index = load_first_example(annotations_df, file_list_df, participant_id, ann_completed, current_index)
+
+    participant_id = gr.Textbox(label='What is your participant ID?', value = participant_id, interactive = False)
+    lets_go = gr.Button("Participant selected!", interactive = False)
+    
+    sentence_text = gr.Textbox(label="Transcription", interactive=False, value = sentence)
+    emotions = gr.Radio(["Blank", "Happy", "Sad", "Angry", "Neutral"], label="Predominant Emotion (Check the sidebar for major subclasses)", value =  emotions, visible = True)
+    confidence = gr.Radio(["Blank","Very Uncertain", "Somewhat Uncertain", "Neutral", "Somewhat confident", "Very confident"], label="How confident are you that the annotated emotion is present in the recording?", visible = True, value = confidence)
+    comments = gr.Textbox(label="Comments", visible =True, value = comments)
+    previous_button = gr.Button("Previous Example", visible = True)
+    next_button = gr.Button("Next Example",visible = True)
+    
+    return annotations_df, file_list_df, participant_id, participant_id, lets_go, total, previous_button, next_button, sentence_text, audio_player, emotions, confidence, comments, n_clicks, start, end, duration, ann_completed, current_index

saved_dictionary.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a2b985bf5b3423dfb3cd235f1ed7f4b44c3bbb606f10beb402d83e220ede8989
+size 23