update

app.py

@@ -1,133 +1,15 @@
-# import math
-# from datasets import load_dataset
-# import gradio as gr
-# import os
-#
-# # auth_token = os.environ.get("auth_token")
-# auth_token = os.environ.get("HF_TOKEN")
-# Visual_Riddles = load_dataset("nitzanguetta/Visual_Riddles", token=auth_token, trust_remote_code=True)['test']
-# # print(f"Loaded WHOOPS!, first example:")
-# # print(whoops[0])
-# dataset_size = len(Visual_Riddles)
-#
-# IMAGE = 'Image'
-# QUESTION = 'Question'
-# ANSWER = "Answer"
-# CAPTION = "Image caption"
-# PROMPT = "Prompt"
-# MODEL_NAME = "Model name"
-# HINT = "Hint"
-# ATTRIBUTION = "Attribution"
-# DLI = "Difficulty Level Index"
-# CATEGORY = "Category"
-# DESIGNER = "Designer"
-#
-#
-# left_side_columns = [IMAGE]
-# right_side_columns = [x for x in Visual_Riddles.features.keys() if x not in left_side_columns]
-# right_side_columns.remove('Image file name')
-# # right_side_columns.remove('Question')
-# # enumerate_cols = [CROWD_CAPTIONS, CROWD_EXPLANATIONS, CROWD_UNDERSPECIFIED_CAPTIONS]
-# emoji_to_label = {IMAGE: '🎨, 🧑‍🎨, 💻', ANSWER: '💡, 🤔, 🧑‍🎨', QUESTION: '❓, 🤔, 💡', CATEGORY: '🤔, 📚, 💡',
-#                   CAPTION: '📝, 👌, 💬', PROMPT: '📝, 💻', MODEL_NAME: '🎨, 💻', HINT:'🤔, 🔍',
-#                   ATTRIBUTION: '🔍, 📄', DLI:"🌡️, 🤔, 🎯", DESIGNER:"🧑‍🎨"}
-# # batch_size = 16
-# batch_size = 8
-# target_size = (1024, 1024)
-#
-#
-# def func(index):
-#     start_index = index * batch_size
-#     end_index = start_index + batch_size
-#     all_examples = [Visual_Riddles[index] for index in list(range(start_index, end_index))]
-#     values_lst = []
-#     for example_idx, example in enumerate(all_examples):
-#         values = get_instance_values(example)
-#         values_lst += values
-#     return values_lst
-#
-#
-# def get_instance_values(example):
-#     values = []
-#     for k in left_side_columns + right_side_columns:
-#         if k == IMAGE:
-#             value = example["Image"].resize(target_size)
-#         # elif k in enumerate_cols:
-#         #     value = list_to_string(example[k])
-#         # elif k == QA:
-#         #     qa_list = [f"Q: {x[0]} A: {x[1]}" for x in example[k]]
-#         #     value = list_to_string(qa_list)
-#         else:
-#             value = example[k]
-#         values.append(value)
-#     return values
-# def list_to_string(lst):
-#     return '\n'.join(['{}. {}'.format(i+1, item) for i, item in enumerate(lst)])
-#
-# demo = gr.Blocks()
-#
-#
-# def get_col(example):
-#     instance_values = get_instance_values(example)
-#     with gr.Column():
-#         inputs_left = []
-#         assert len(left_side_columns) == len(
-#             instance_values[:len(left_side_columns)])  # excluding the image & designer
-#         for key, value in zip(left_side_columns, instance_values[:len(left_side_columns)]):
-#             if key == IMAGE:
-#                 img_resized = example["Image"].resize(target_size)
-#                 # input_k = gr.Image(value=img_resized, label=example['commonsense_category'])
-#                 input_k = gr.Image(value=img_resized)
-#             else:
-#                 label = key.capitalize().replace("_", " ")
-#                 input_k = gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}")
-#             inputs_left.append(input_k)
-#         with gr.Accordion("Click for details", open=False):
-#         # with gr.Accordion(example[QUESTION], open=False):
-#             text_inputs_right = []
-#             assert len(right_side_columns) == len(
-#                 instance_values[len(left_side_columns):])  # excluding the image & designer
-#             for key, value in zip(right_side_columns, instance_values[len(left_side_columns):]):
-#                 label = key.capitalize().replace("_", " ")
-#                 num_lines = max(1, len(value) // 50 + (len(value) % 50 > 0))  # Assuming ~50 chars per line
-#                 text_input_k = gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}", lines=num_lines)
-#                 text_inputs_right.append(text_input_k)
-#     return inputs_left, text_inputs_right
-#
-#
-# with demo:
-#     gr.Markdown("# Slide to iterate Visual Riddles")
-#
-#     with gr.Column():
-#         num_batches = math.ceil(dataset_size / batch_size)
-#         slider = gr.Slider(minimum=0, maximum=num_batches, step=1, label=f'Page (out of {num_batches})')
-#         with gr.Row():
-#             index = slider.value
-#             start_index = 0 * batch_size
-#             end_index = start_index + batch_size
-#             all_examples = [Visual_Riddles[index] for index in list(range(start_index, end_index))]
-#             all_inputs_left_right = []
-#             for example_idx, example in enumerate(all_examples):
-#                 inputs_left, text_inputs_right = get_col(example)
-#                 inputs_left_right = inputs_left + text_inputs_right
-#                 all_inputs_left_right += inputs_left_right
-#
-#     slider.change(func, inputs=[slider], outputs=all_inputs_left_right)
-#
-# demo.launch()
-
-
 import math
 from datasets import load_dataset
 import gradio as gr
 import os
 
-# Set up environment variables and load dataset
+# auth_token = os.environ.get("auth_token")
 auth_token = os.environ.get("HF_TOKEN")
 Visual_Riddles = load_dataset("nitzanguetta/Visual_Riddles", token=auth_token, trust_remote_code=True)['test']
+# print(f"Loaded WHOOPS!, first example:")
+# print(whoops[0])
 dataset_size = len(Visual_Riddles)
 
-# Define attributes
 IMAGE = 'Image'
 QUESTION = 'Question'
 ANSWER = "Answer"
@@ -140,19 +22,20 @@ DLI = "Difficulty Level Index"
 CATEGORY = "Category"
 DESIGNER = "Designer"
 
+
 left_side_columns = [IMAGE]
 right_side_columns = [x for x in Visual_Riddles.features.keys() if x not in left_side_columns]
 right_side_columns.remove('Image file name')
-
-emoji_to_label = {
-    IMAGE: '🎨, 🧑‍🎨, 💻', ANSWER: '💡, 🤔, 🧑‍🎨', QUESTION: '❓, 🤔, 💡', CATEGORY: '🤔, 📚, 💡',
-    CAPTION: '📝, 👌, 💬', PROMPT: '📝, 💻', MODEL_NAME: '🎨, 💻', HINT:'🤔, 🔍',
-    ATTRIBUTION: '🔍, 📄', DLI:"🌡️, 🤔, 🎯", DESIGNER:"🧑‍🎨"
-}
-
+# right_side_columns.remove('Question')
+# enumerate_cols = [CROWD_CAPTIONS, CROWD_EXPLANATIONS, CROWD_UNDERSPECIFIED_CAPTIONS]
+emoji_to_label = {IMAGE: '🎨, 🧑‍🎨, 💻', ANSWER: '💡, 🤔, 🧑‍🎨', QUESTION: '❓, 🤔, 💡', CATEGORY: '🤔, 📚, 💡',
+                  CAPTION: '📝, 👌, 💬', PROMPT: '📝, 💻', MODEL_NAME: '🎨, 💻', HINT:'🤔, 🔍',
+                  ATTRIBUTION: '🔍, 📄', DLI:"🌡️, 🤔, 🎯", DESIGNER:"🧑‍🎨"}
+# batch_size = 16
 batch_size = 8
 target_size = (1024, 1024)
 
+
 def func(index):
     start_index = index * batch_size
     end_index = start_index + batch_size
@@ -163,51 +46,173 @@ def func(index):
         values_lst += values
     return values_lst
 
-# Define functions to handle data and interface
+
 def get_instance_values(example):
     values = []
     for k in left_side_columns + right_side_columns:
         if k == IMAGE:
             value = example["Image"].resize(target_size)
+        # elif k in enumerate_cols:
+        #     value = list_to_string(example[k])
+        # elif k == QA:
+        #     qa_list = [f"Q: {x[0]} A: {x[1]}" for x in example[k]]
+        #     value = list_to_string(qa_list)
         else:
             value = example[k]
         values.append(value)
     return values
+def list_to_string(lst):
+    return '\n'.join(['{}. {}'.format(i+1, item) for i, item in enumerate(lst)])
+
+demo = gr.Blocks()
+
 
 def get_col(example):
     instance_values = get_instance_values(example)
-    inputs_left, text_inputs_right = [], []
-    with gr.Column() as col:
+    with gr.Column():
+        inputs_left = []
+        assert len(left_side_columns) == len(
+            instance_values[:len(left_side_columns)])  # excluding the image & designer
         for key, value in zip(left_side_columns, instance_values[:len(left_side_columns)]):
             if key == IMAGE:
                 img_resized = example["Image"].resize(target_size)
+                # input_k = gr.Image(value=img_resized, label=example['commonsense_category'])
                 input_k = gr.Image(value=img_resized)
             else:
                 label = key.capitalize().replace("_", " ")
                 input_k = gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}")
             inputs_left.append(input_k)
         with gr.Accordion("Click for details", open=False):
+        # with gr.Accordion(example[QUESTION], open=False):
+            text_inputs_right = []
+            assert len(right_side_columns) == len(
+                instance_values[len(left_side_columns):])  # excluding the image & designer
             for key, value in zip(right_side_columns, instance_values[len(left_side_columns):]):
                 label = key.capitalize().replace("_", " ")
-                num_lines = max(1, len(value) // 50 + (len(value) % 50 > 0))
+                num_lines = max(1, len(value) // 50 + (len(value) % 50 > 0))  # Assuming ~50 chars per line
                 text_input_k = gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}", lines=num_lines)
                 text_inputs_right.append(text_input_k)
     return inputs_left, text_inputs_right
 
-# Create the Gradio Blocks interface
-with gr.Blocks() as demo:
-    with gr.Row():
-        gr.Markdown("# Visual Riddles Explorer")
+
+with demo:
+    gr.Markdown("# Slide to iterate Visual Riddles")
+
     with gr.Column():
         num_batches = math.ceil(dataset_size / batch_size)
-        slider = gr.Slider(minimum=0, maximum=num_batches - 1, step=1, label=f'Page (out of {num_batches})')
-        slider.change(lambda x: get_col(Visual_Riddles[x * batch_size]), inputs=[slider], outputs=[gr.Row()])
+        slider = gr.Slider(minimum=0, maximum=num_batches, step=1, label=f'Page (out of {num_batches})')
+        with gr.Row():
+            index = slider.value
+            start_index = 0 * batch_size
+            end_index = start_index + batch_size
+            all_examples = [Visual_Riddles[index] for index in list(range(start_index, end_index))]
+            all_inputs_left_right = []
+            for example_idx, example in enumerate(all_examples):
+                inputs_left, text_inputs_right = get_col(example)
+                inputs_left_right = inputs_left + text_inputs_right
+                all_inputs_left_right += inputs_left_right
+
+    slider.change(func, inputs=[slider], outputs=all_inputs_left_right)
 
-# Define credentials for authentication
+# demo.launch()
 credentials = [
-    ("user", "Aa123"),
-    ("username2", "password2")
+    ("Viri", "Aa123")
 ]
 
 # Launch the interface with password protection
 demo.launch(auth=credentials)
+
+# import math
+# from datasets import load_dataset
+# import gradio as gr
+# import os
+#
+# # Set up environment variables and load dataset
+# auth_token = os.environ.get("HF_TOKEN")
+# Visual_Riddles = load_dataset("nitzanguetta/Visual_Riddles", token=auth_token, trust_remote_code=True)['test']
+# dataset_size = len(Visual_Riddles)
+#
+# # Define attributes
+# IMAGE = 'Image'
+# QUESTION = 'Question'
+# ANSWER = "Answer"
+# CAPTION = "Image caption"
+# PROMPT = "Prompt"
+# MODEL_NAME = "Model name"
+# HINT = "Hint"
+# ATTRIBUTION = "Attribution"
+# DLI = "Difficulty Level Index"
+# CATEGORY = "Category"
+# DESIGNER = "Designer"
+#
+# left_side_columns = [IMAGE]
+# right_side_columns = [x for x in Visual_Riddles.features.keys() if x not in left_side_columns]
+# right_side_columns.remove('Image file name')
+#
+# emoji_to_label = {
+#     IMAGE: '🎨, 🧑‍🎨, 💻', ANSWER: '💡, 🤔, 🧑‍🎨', QUESTION: '❓, 🤔, 💡', CATEGORY: '🤔, 📚, 💡',
+#     CAPTION: '📝, 👌, 💬', PROMPT: '📝, 💻', MODEL_NAME: '🎨, 💻', HINT:'🤔, 🔍',
+#     ATTRIBUTION: '🔍, 📄', DLI:"🌡️, 🤔, 🎯", DESIGNER:"🧑‍🎨"
+# }
+#
+# batch_size = 8
+# target_size = (1024, 1024)
+#
+# def func(index):
+#     start_index = index * batch_size
+#     end_index = start_index + batch_size
+#     all_examples = [Visual_Riddles[index] for index in list(range(start_index, end_index))]
+#     values_lst = []
+#     for example_idx, example in enumerate(all_examples):
+#         values = get_instance_values(example)
+#         values_lst += values
+#     return values_lst
+#
+# # Define functions to handle data and interface
+# def get_instance_values(example):
+#     values = []
+#     for k in left_side_columns + right_side_columns:
+#         if k == IMAGE:
+#             value = example["Image"].resize(target_size)
+#         else:
+#             value = example[k]
+#         values.append(value)
+#     return values
+#
+# def get_col(example):
+#     instance_values = get_instance_values(example)
+#     inputs_left, text_inputs_right = [], []
+#     with gr.Column() as col:
+#         for key, value in zip(left_side_columns, instance_values[:len(left_side_columns)]):
+#             if key == IMAGE:
+#                 img_resized = example["Image"].resize(target_size)
+#                 input_k = gr.Image(value=img_resized)
+#             else:
+#                 label = key.capitalize().replace("_", " ")
+#                 input_k = gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}")
+#             inputs_left.append(input_k)
+#         with gr.Accordion("Click for details", open=False):
+#             for key, value in zip(right_side_columns, instance_values[len(left_side_columns):]):
+#                 label = key.capitalize().replace("_", " ")
+#                 num_lines = max(1, len(value) // 50 + (len(value) % 50 > 0))
+#                 text_input_k = gr.Textbox(value=value, label=f"{label} {emoji_to_label[key]}", lines=num_lines)
+#                 text_inputs_right.append(text_input_k)
+#     return inputs_left, text_inputs_right
+#
+# # Create the Gradio Blocks interface
+# with gr.Blocks() as demo:
+#     with gr.Row():
+#         gr.Markdown("# Visual Riddles Explorer")
+#     with gr.Column():
+#         num_batches = math.ceil(dataset_size / batch_size)
+#         slider = gr.Slider(minimum=0, maximum=num_batches - 1, step=1, label=f'Page (out of {num_batches})')
+#         slider.change(lambda x: get_col(Visual_Riddles[x * batch_size]), inputs=[slider], outputs=[gr.Row()])
+#
+# # Define credentials for authentication
+# credentials = [
+#     ("user", "Aa123"),
+#     ("username2", "password2")
+# ]
+#
+# # Launch the interface with password protection
+# demo.launch(auth=credentials)