update app to support additional IIW data release sets.

app.py

@@ -1,18 +1,55 @@
-import os
 import gradio as gr
-from datasets import load_dataset
+import logging
 import random
+import os
+
+from datasets import load_dataset
+from huggingface_hub import login
+
+try:
+    login()
+except:
+    pass
+
+auth_token = os.environ.get('HF_TOKEN', None)
+if not auth_token:
+    raise ValueError("could not authenticate the user.")
+
+iiw_400 = load_dataset('google/imageinwords', token=auth_token, trust_remote_code=True, name="IIW-400")
+docci_test = load_dataset('google/imageinwords', token=auth_token, trust_remote_code=True, name="DOCCI_Test")
+locnar_eval = load_dataset('google/imageinwords', token=auth_token, trust_remote_code=True, name="LocNar_Eval")
+cm_3600 = load_dataset('google/imageinwords', token=auth_token, trust_remote_code=True, name="CM_3600")
+
+_SELECTOR_TO_DATASET = {
+    "IIW-400": iiw_400,
+    "DOCCI_Test": docci_test,
+    "LocNar_Eval": locnar_eval,
+    "CM_3600": cm_3600
+}
 
-auth_token = os.environ.get("auth_token")
-iiw_400 = load_dataset('google/imageinwords', token=auth_token, name="IIW-400")
 
-def display_iiw_data(index):
-    data = iiw_400['test'][index]
-    image_html = f'<img src="{data["image/url"]}" style="width:100%; max-width:800px; height:auto;">'
-    iiw_text = f"<h2>IIW Human Descriptions:</h2><p style='font-size: 16px'>{data['IIW']}</p>"
-    iiw_p5b_text = f"<h2>IIW PaLI 5B Predictions:</h2><p style='font-size: 16px'>{data['IIW-P5B']}</p>"
-    ratings = "<h2>Ratings:</h2>"
-    if data['iiw-human-sxs-iiw-p5b'] is not None:
+def display_iiw_data_with_slider_change(dataset_type, index):
+    dataset_split, image_key, image_url_key = "test", "image/key", "image/url"
+    if dataset_type == "LocNar_Eval":
+        dataset_split = "validation"
+    if dataset_type == "DOCCI_Test":
+        image_url_key = "image/thumbnail_url"
+        image_key = "image"
+
+    logging.warning(f"SELECTION: {dataset_type} : {dataset_split}: {index}")
+    data = _SELECTOR_TO_DATASET[dataset_type][dataset_split][index]
+    image_html = f'<img src="{data[image_url_key]}" style="width:100%; max-width:800px; height:auto;">'
+    image_key_html = f"<p style='font-size: 10px'>Image Key: {data[image_key]}</p>"
+
+    iiw_text, iiw_p5b_text, ratings = "", "", ""
+    if "IIW" in data:
+        iiw_text = f"<h2>IIW Human-Authored Descriptions</h2><p style='font-size: 16px'>{data['IIW']}</p>"
+
+    if "IIW-P5B" in data:
+        iiw_p5b_text = f"<h2>IIW PaLI-5B Generated Descriptions</h2><p style='font-size: 16px'>{data['IIW-P5B']}</p>"
+    
+    if 'iiw-human-sxs-iiw-p5b' in data and data['iiw-human-sxs-iiw-p5b'] is not None:
+        ratings = "<h2>Ratings</h2>"
         for key, value in data['iiw-human-sxs-iiw-p5b'].items():
             key = key.split("metrics/")[-1]
             emoji = ""
@@ -27,30 +64,47 @@ def display_iiw_data(index):
             elif key == "Human Like":
                 emoji = "👤"  # Bust in Silhouette
             ratings += f"<p style='font-size: 16px'>{emoji} <strong>{key}</strong>: {value}</p>"
-    return image_html, iiw_text, iiw_p5b_text, ratings
+    return image_key_html, image_html, iiw_text, iiw_p5b_text, ratings
+
+
+def display_iiw_data_with_dataset_change(dataset_type, index):
+    slider = gr.Slider(minimum=0, maximum=max_index(dataset_type)-1, label="Dataset Size", value=0)
+    image_key_html, image_html, iiw_text, iiw_p5b_text, ratings = display_iiw_data_with_slider_change(dataset_type, index=0)
+    return slider, image_key_html, image_html, iiw_text, iiw_p5b_text, ratings
+
+
+def max_index(dataset_type):
+    dataset_split = "test"
+    if dataset_type == "LocNar_Eval":
+        dataset_split = "validation"
+
+    logging.warning(f"SELECTION: {dataset_type} : {dataset_split}")
+    dataset_instance =_SELECTOR_TO_DATASET[dataset_type][dataset_split]
+    return len(dataset_instance)
 
-def random_index():
-    while True:
-        index = random.randint(0, len(iiw_400['test']) - 1)
-        if iiw_400['test'][index]['iiw-human-sxs-iiw-p5b'] is not None:
-            return index
 
-demo = gr.Blocks()
+with gr.Blocks() as demo:
+    gr.Markdown("# ImageInWords: Unlocking Hyper-Detailed Image Descriptions")
+    gr.Markdown("Slide across the slider to see various examples across the different IIW datasets.")
 
-with demo:
-    gr.Markdown("# Slide across the slider to see various examples from IIW-400")
+    with gr.Row():
+        dataset_selector = gr.Radio(["IIW-400", "DOCCI_Test", "LocNar_Eval", "CM_3600"], value="IIW-400", label="IIW Datasets")
+        slider, image_key_html, image_html, iiw_text, iiw_p5b_text, ratings = display_iiw_data_with_dataset_change(dataset_selector.value, index=0)
 
-    with gr.Column():
-        slider = gr.Slider(minimum=0, maximum=400)
-        with gr.Row():
-            index = random_index()
-            with gr.Column():
-                image_output = gr.HTML(display_iiw_data(index)[0])
-            with gr.Column():
-                iiw_text_output = gr.HTML(display_iiw_data(index)[1])
-                iiw_p5b_text_output = gr.HTML(display_iiw_data(index)[2])
-                ratings_output = gr.HTML(display_iiw_data(index)[3])
+    with gr.Row():
+        with gr.Column():
+            image_output = gr.HTML(image_html)
+        
+        with gr.Column():
+            image_key_output = gr.HTML(image_key_html)
+            if iiw_text:
+                iiw_text_output = gr.HTML(iiw_text)
+            if iiw_p5b_text:
+                iiw_p5b_text_output = gr.HTML(iiw_p5b_text)
+            if ratings:
+                ratings_output = gr.HTML(ratings)
 
-    slider.change(display_iiw_data, inputs=[slider], outputs=[image_output, iiw_text_output, iiw_p5b_text_output, ratings_output])
+    slider.change(display_iiw_data_with_slider_change, inputs=[dataset_selector, slider], outputs=[image_key_output, image_output, iiw_text_output, iiw_p5b_text_output, ratings_output])
+    dataset_selector.change(display_iiw_data_with_dataset_change, inputs=[dataset_selector, slider], outputs=[slider, image_key_output, image_output, iiw_text_output, iiw_p5b_text_output, ratings_output])
 
-demo.launch(debug=True)
+demo.launch(debug=True)