vote interface

app.py

@@ -5,19 +5,22 @@ Main Gradio module.
 import gradio as gr
 
 from src import (
-    explore_interface,
     label_interface,
+    sample_interface,
+    vote_interface,
 )
 
 
 demo = gr.TabbedInterface(
     [
-        explore_interface.interface,
         label_interface.interface,
+        sample_interface.interface,
+        vote_interface.interface,
     ],
     [
-        "Explore",
         "Label",
+        "Sample",
+        "Vote",
     ],
     title="Explore & Label Concepts",
     analytics_enabled=True,

src/explore_interface.py

@@ -1,74 +0,0 @@
-"""Interface to explore images and labels.
-"""
-
-import random
-
-import gradio as gr
-
-from src import global_variables
-from src.constants import CONCEPTS, ASSETS_FOLDER, DATASET_NAME
-
-def get_next_image(
-    split: str,
-    concepts: list,
-    current_metadata: dict,
-    selected_concepts: list,
-):
-    if concepts != selected_concepts:
-        for split, values in global_variables.all_metadata.items():
-            current_metadata[split] = [x for x in values if all([c in x["concepts"] for c in concepts])]
-        selected_concepts = concepts
-    try:
-        if split == "all":
-            sample = random.choice(
-                current_metadata["train"] + current_metadata["validation"] + current_metadata["test"]
-            )
-        else:
-            sample = random.choice(current_metadata[split])
-        image_path = f"{ASSETS_FOLDER}/{DATASET_NAME}/data/{split}/{sample['file_name']}"
-        return image_path, sample["class"], sample["concepts"], current_metadata, selected_concepts
-    except IndexError:
-        gr.Warning("No image found for the selected filter.")
-        return None, None, None, current_metadata, selected_concepts
-
-with gr.Blocks() as interface:        
-    with gr.Row():
-        with gr.Column():
-            with gr.Group():
-                gr.Markdown(
-                    "## # Image Selection",
-                )
-                split = gr.Radio(
-                    label="Split",
-                    choices=["train", "validation", "test", "all"],
-                    value="train",
-                )
-                concepts = gr.Dropdown(
-                    label="Concepts",
-                    multiselect=True,
-                    choices=CONCEPTS,
-                )
-            button = gr.Button(
-                value="Next",
-            )
-            with gr.Group():
-                gr.Markdown(
-                    "##  # Image Info",
-                )
-                im_class = gr.Textbox(
-                    label="Class",
-                )
-                im_concepts = gr.JSON(
-                    label="Concepts",
-                )
-        with gr.Column():
-            image = gr.Image(
-                label="Image",
-            )
-    current_metadata = gr.State(global_variables.all_metadata)
-    selected_concepts = gr.State([])
-    button.click(
-        get_next_image, 
-        outputs=[image, im_class, im_concepts, current_metadata, selected_concepts], 
-        inputs=[split, concepts, current_metadata, selected_concepts]
-    )

src/label_interface.py

@@ -12,11 +12,18 @@ from src.constants import CONCEPTS, ASSETS_FOLDER, DATASET_NAME
 
 def get_next_image(
     split: str,
+    concepts: list,
+    filtered_indices: dict,
+    selected_concepts: list,
     profile: gr.OAuthProfile
 ):
     username = profile.username
+    if concepts != selected_concepts:
+        for key, values in global_variables.all_metadata.items():
+            filtered_indices[key] = [i for i in range(len(values)) if all([values[i]["concepts"].get(c, False) for c in concepts])]
+        selected_concepts = concepts
     try:
-        sample_idx = random.choice(range(len(global_variables.all_metadata[split])))
+        sample_idx = random.choice(filtered_indices[split])
         sample = global_variables.all_metadata[split][sample_idx]
         image_path = f"{ASSETS_FOLDER}/{DATASET_NAME}/data/{split}/{sample['file_name']}"
         try:
@@ -25,37 +32,56 @@ def get_next_image(
         except KeyError:
             voted_concepts = []
 
-        return image_path, voted_concepts, f"{split}:{sample_idx}"
+        return (
+            image_path, 
+            voted_concepts, 
+            f"{split}:{sample_idx}", 
+            sample["class"], 
+            sample["concepts"],
+            filtered_indices, 
+            selected_concepts,
+        )
     except IndexError:
         gr.Warning("No image found for the selected filter.")
-        return None, None, None
+        return None, None, None, None, None, filtered_indices, selected_concepts
 
 def submit_label(
     voted_concepts: list,
     current_image: Optional[str],
+    split, 
+    concepts, 
+    filtered_indices, 
+    selected_concepts,
     profile: gr.OAuthProfile
 ):
     username = profile.username
     if current_image is None:
         gr.Warning("No image selected.")
-        return None, None, None
-    split, idx = current_image.split(":")
+        return None, None, None, None, None, filtered_indices, selected_concepts
+    current_split, idx = current_image.split(":")
     idx = int(idx)
-    global_variables.get_metadata(split)
-    if "votes" not in global_variables.all_metadata[split][idx]:
-        global_variables.all_metadata[split][idx]["votes"] = {}
-    global_variables.all_metadata[split][idx]["votes"][username] = {c: c in voted_concepts for c in CONCEPTS}
+    global_variables.get_metadata(current_split)
+    if "votes" not in global_variables.all_metadata[current_split][idx]:
+        global_variables.all_metadata[current_split][idx]["votes"] = {}
+    global_variables.all_metadata[current_split][idx]["votes"][username] = {c: c in voted_concepts for c in CONCEPTS}
     vote_sum = {c: 0 for c in CONCEPTS}
     concepts = {}
     for c in CONCEPTS:
-        for vote in global_variables.all_metadata[split][idx]["votes"].values():
+        for vote in global_variables.all_metadata[current_split][idx]["votes"].values():
             if c not in vote:
                 continue
             vote_sum[c] += 2 * vote[c] - 1
         concepts[c] = vote_sum[c] > 0 if vote_sum[c] != 0 else None
-    global_variables.all_metadata[split][idx]["concepts"] = concepts
-    global_variables.save_metadata(split)
-    return get_next_image(split, profile)
+    global_variables.all_metadata[current_split][idx]["concepts"] = concepts
+    global_variables.save_metadata(current_split)
+    gr.Info("Submit success")
+    return get_next_image(
+        split, 
+        concepts,
+        filtered_indices,
+        selected_concepts,
+        profile
+    )
     
 
 with gr.Blocks() as interface:
@@ -67,14 +93,20 @@ with gr.Blocks() as interface:
                 )
                 split = gr.Radio(
                     label="Split",
-                    choices=["train", "validation", "test",],
+                    choices=["train", "validation", "test"],
                     value="train",
                 )
+                concepts = gr.Dropdown(
+                    label="Concepts",
+                    multiselect=True,
+                    choices=CONCEPTS,
+                )
             with gr.Group():
                 voted_concepts = gr.CheckboxGroup(
-                    label="Concepts",
+                    label="Voted Concepts",
                     choices=CONCEPTS,
                 )
+
             with gr.Row():
                 next_button = gr.Button(
                     value="Next",
@@ -83,19 +115,42 @@ with gr.Blocks() as interface:
                 submit_button = gr.Button(
                     value="Submit",
                 )
-
+            with gr.Group():
+                gr.Markdown(
+                    "##  # Image Info",
+                )
+                im_class = gr.Textbox(
+                    label="Class",
+                )
+                im_concepts = gr.JSON(
+                    label="Concepts",
+                )
         with gr.Column():
             image = gr.Image(
                 label="Image",
             )
     current_image = gr.State(None)
+    filtered_indices = gr.State({
+        split: list(range(len(global_variables.all_metadata[split])))
+        for split in global_variables.all_metadata
+    })
+    selected_concepts = gr.State([])
+    common_output = [
+        image, 
+        voted_concepts, 
+        current_image, 
+        im_class,
+        im_concepts,
+        filtered_indices, 
+        selected_concepts
+    ]
     next_button.click(
         get_next_image, 
-        inputs=[split],
-        outputs=[image, voted_concepts, current_image],
+        inputs=[split, concepts, filtered_indices, selected_concepts],
+        outputs=common_output
     )
     submit_button.click(
         submit_label,
-        inputs=[voted_concepts, current_image],
-        outputs=[image, voted_concepts, current_image],
+        inputs=[voted_concepts, current_image, split, concepts, filtered_indices, selected_concepts],
+        outputs=common_output
     )

src/sample_interface.py

@@ -0,0 +1,187 @@
+"""Interface for labeling concepts in images.
+"""
+
+from typing import Optional
+
+import gradio as gr
+
+from src import global_variables
+from src.constants import CONCEPTS, ASSETS_FOLDER, DATASET_NAME
+
+def get_image(
+    step: int,
+    split: str,
+    index: str,
+    filtered_indices: dict,
+    profile: gr.OAuthProfile
+):
+    username = profile.username
+    try:
+        int_index = int(index)
+    except:
+        gr.Warning("Error parsing index using 0")
+        int_index = 0
+    sample_idx = int_index + step
+    if sample_idx < 0:
+        gr.Warning("No previous image.")
+        sample_idx = 0
+    if sample_idx >= len(global_variables.all_metadata[split]):
+        gr.Warning("No next image.")
+        sample_idx = len(global_variables.all_metadata[split]) - 1
+    sample = global_variables.all_metadata[split][sample_idx]
+    image_path = f"{ASSETS_FOLDER}/{DATASET_NAME}/data/{split}/{sample['file_name']}"
+    try:
+        username_votes = sample["votes"][username]
+        voted_concepts = [c for c in CONCEPTS if username_votes.get(c, False)]
+    except KeyError:
+        voted_concepts = []
+
+    return (
+        image_path, 
+        voted_concepts, 
+        f"{split}:{sample_idx}", 
+        sample["class"], 
+        sample["concepts"],
+        str(sample_idx),
+        filtered_indices, 
+    )
+
+def make_get_image(step):
+    def f(
+        split: str,
+        index: str,
+        filtered_indices: dict,
+        profile: gr.OAuthProfile 
+    ):
+        return get_image(step, split, index, filtered_indices, profile)
+    return f
+
+get_next_image = make_get_image(1)
+get_prev_image = make_get_image(-1)
+get_current_image = make_get_image(0)
+
+def submit_label(
+    voted_concepts: list,
+    current_image: Optional[str],
+    split, 
+    index,
+    filtered_indices, 
+    profile: gr.OAuthProfile
+):
+    username = profile.username
+    if current_image is None:
+        gr.Warning("No image selected.")
+        return None, None, None, None, None, index, filtered_indices
+    current_split, idx = current_image.split(":")
+    idx = int(idx)
+    global_variables.get_metadata(current_split)
+    if "votes" not in global_variables.all_metadata[current_split][idx]:
+        global_variables.all_metadata[current_split][idx]["votes"] = {}
+    global_variables.all_metadata[current_split][idx]["votes"][username] = {c: c in voted_concepts for c in CONCEPTS}
+    vote_sum = {c: 0 for c in CONCEPTS}
+    concepts = {}
+    for c in CONCEPTS:
+        for vote in global_variables.all_metadata[current_split][idx]["votes"].values():
+            if c not in vote:
+                continue
+            vote_sum[c] += 2 * vote[c] - 1
+        concepts[c] = vote_sum[c] > 0 if vote_sum[c] != 0 else None
+    global_variables.all_metadata[current_split][idx]["concepts"] = concepts
+    global_variables.save_metadata(current_split)
+    gr.Info("Submit success")
+    return get_next_image(
+        split, 
+        index,
+        filtered_indices,
+        profile
+    )
+    
+
+with gr.Blocks() as interface:
+    with gr.Row():
+        with gr.Column():
+            with gr.Group():
+                gr.Markdown(
+                    "## # Image Selection",
+                )
+                split = gr.Radio(
+                    label="Split",
+                    choices=["train", "validation", "test"],
+                    value="train",
+                )
+                index = gr.Textbox(
+                    value="0",
+                    label="Index",
+                    max_lines=1,
+                )
+            with gr.Group():
+                voted_concepts = gr.CheckboxGroup(
+                    label="Voted Concepts",
+                    choices=CONCEPTS,
+                )
+
+            with gr.Row():
+                prev_button = gr.Button(
+                    value="Prev",
+                )
+                next_button = gr.Button(
+                    value="Next",
+                )
+                gr.LoginButton()
+                submit_button = gr.Button(
+                    value="Submit",
+                )
+            with gr.Group():
+                gr.Markdown(
+                    "##  # Image Info",
+                )
+                im_class = gr.Textbox(
+                    label="Class",
+                )
+                im_concepts = gr.JSON(
+                    label="Concepts",
+                )
+        with gr.Column():
+            image = gr.Image(
+                label="Image",
+            )
+    current_image = gr.State(None)
+    filtered_indices = gr.State({
+        split: list(range(len(global_variables.all_metadata[split])))
+        for split in global_variables.all_metadata
+    })
+    common_output = [
+        image, 
+        voted_concepts, 
+        current_image, 
+        im_class,
+        im_concepts,
+        index,
+        filtered_indices, 
+    ]
+    common_input = [split, index, filtered_indices]
+    prev_button.click(
+        get_prev_image, 
+        inputs=common_input,
+        outputs=common_output
+    )
+    next_button.click(
+        get_next_image, 
+        inputs=common_input,
+        outputs=common_output
+    )
+    submit_button.click(
+        submit_label,
+        inputs=[voted_concepts, current_image, split, index, filtered_indices],
+        outputs=common_output
+    )
+    index.submit(
+        get_current_image,
+        inputs=common_input,
+        outputs=common_output,
+    )
+    interface.load(
+        get_current_image,
+        inputs=common_input,
+        outputs=common_output,
+    )

src/vote_interface.py

@@ -0,0 +1,49 @@
+"""Interface for labeling concepts in images.
+"""
+
+import gradio as gr
+
+from src import global_variables
+
+
+def get_votes(
+    split, 
+    profile: gr.OAuthProfile
+):
+    username = profile.username
+    vote_list = []
+    for i,s in enumerate(global_variables.all_metadata[split]):
+        if "votes" in s and username in s["votes"]:
+            vote_list.append(f'[{i}]: {s["votes"][username]}')
+    
+    return "\n".join(vote_list)
+    
+
+with gr.Blocks() as interface:
+    with gr.Row():
+        with gr.Column():
+            with gr.Group():
+                gr.Markdown(
+                    "## # Selection",
+                )
+                split = gr.Radio(
+                    label="Split",
+                    choices=["train", "validation", "test"],
+                    value="train",
+                )
+
+            with gr.Row():
+                gr.LoginButton()
+                get_button = gr.Button(
+                    value="Get My Votes",
+                )
+        with gr.Column():
+            votes = gr.TextArea(
+                label="Votes",
+                lines=1,
+            )
+    get_button.click(
+        get_votes,
+        inputs=[split],
+        outputs=[votes]
+    )