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README.md

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+---
+title: Visual Puzzles Annotator
+emoji: 🦀
+colorFrom: indigo
+colorTo: red
+sdk: gradio
+sdk_version: 5.34.0
+app_file: app.py
+pinned: false
+short_description: visual-puzzles-annotator for visual-puzzles website
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import os
+import json
+from PIL import Image
+import tempfile
+from datasets import load_dataset
+
+DATASET_NAME = "Kyunnilee/visual-puzzles"
+SPLIT_NAME = "train"
+
+IMAGE_FOLDER = "images"
+os.makedirs(IMAGE_FOLDER, exist_ok=True)
+
+# Load dataset
+hf_dataset = load_dataset(DATASET_NAME, split=SPLIT_NAME)
+
+image_paths = []
+for i, example in enumerate(hf_dataset):
+    img = example["image"]
+    path = os.path.join(IMAGE_FOLDER, f"image_{i}.png")
+    img.save(path)
+    image_paths.append(f"image_{i}.png")
+
+ANNOTATION_FILE = "annotations.json"
+
+annotations = []
+current_index = 0
+
+
+# Helper functions
+def load_annotations(file_obj):
+    global annotations, current_index
+    file_path = file_obj.name if hasattr(file_obj, "name") else file_obj
+    with open(file_path, "r") as f:
+        annotations = json.load(f)
+    done_images = {a["image"] for a in annotations}
+    remaining = [img for img in image_paths if img not in done_images]
+    current_index = 0 if not remaining else image_paths.index(remaining[0])
+    return update_interface()
+
+
+def save_annotations():
+    with tempfile.NamedTemporaryFile(mode="w+", delete=False, suffix=".json") as tmp:
+        json.dump(annotations, tmp, indent=2)
+        tmp_path = tmp.name
+    return tmp_path
+
+
+def update_interface():
+    if current_index >= len(image_paths):
+        skipped_count = sum(1 for a in annotations if a["answer"] == "<SKIP>")
+        return None, "", f"All {len(image_paths)} images annotated. Skipped: {skipped_count}", 100
+    image_path = os.path.join(IMAGE_FOLDER, image_paths[current_index])
+    existing = next((a["answer"] for a in annotations if a["image"] == image_paths[current_index]), "")
+    skipped_count = sum(1 for a in annotations if a["answer"] == "<SKIP>")
+    return (
+        image_path,
+        existing if existing != "<SKIP>" else "",
+        f"{len(annotations)} / {len(image_paths)} completed. Skipped: {skipped_count}",
+        int((len(annotations) / len(image_paths)) * 100),
+    )
+
+
+def submit_answer(answer):
+    global current_index
+    if current_index < len(image_paths):
+        img_name = image_paths[current_index]
+        existing = next((a for a in annotations if a["image"] == img_name), None)
+        if answer.strip():
+            if existing:
+                existing["answer"] = answer
+            else:
+                annotations.append({"image": img_name, "answer": answer})
+        else:
+            if not existing:
+                annotations.append({"image": img_name, "answer": "<SKIP>"})
+
+    # Find the next unannotated index
+    for i in range(current_index + 1, len(image_paths)):
+        next_img_name = image_paths[i]
+        if not any(a["image"] == next_img_name and a["answer"] not in ("", "<SKIP>") for a in annotations):
+            current_index = i
+            break
+    else:
+        # If no unannotated images are found, set current_index to the end
+        current_index = len(image_paths)
+
+    return update_interface()
+
+
+def go_previous():
+    global current_index
+    if current_index > 0:
+        current_index -= 1
+    return update_interface()
+
+
+def go_next():
+    global current_index
+    if current_index < len(image_paths) - 1:
+        current_index += 1
+    return update_interface()
+
+
+# Gradio Interface
+with gr.Blocks() as demo:
+    gr.Markdown("## Rebus Puzzle Annotator")
+
+    with gr.Row():
+        image_display = gr.Image(label="Rebus Image", type="filepath")
+        textbox = gr.Textbox(label="Your Answer", placeholder="Type the rebus answer here")
+
+    with gr.Row():
+        submit_btn = gr.Button("Submit Answer")
+        prev_btn = gr.Button("Previous")
+        next_btn = gr.Button("Next")
+
+    with gr.Row():
+        status = gr.Textbox(label="Progress")
+        progress_bar = gr.Slider(label="Progress", minimum=0, maximum=100, step=1, interactive=False)
+
+    with gr.Row():
+        download_btn = gr.Button("Export Annotations")
+        upload_btn = gr.File(label="Import Annotations", file_types=[".json"])
+        output_file = gr.File(label="Download JSON")
+
+    # Hook up events
+    submit_btn.click(submit_answer, textbox, [image_display, textbox, status, progress_bar])
+    textbox.submit(submit_answer, textbox, [image_display, textbox, status, progress_bar])
+    prev_btn.click(go_previous, None, [image_display, textbox, status, progress_bar])
+    next_btn.click(go_next, None, [image_display, textbox, status, progress_bar])
+    download_btn.click(save_annotations, None, output_file)
+    upload_btn.change(load_annotations, upload_btn, [image_display, textbox, status, progress_bar])
+
+    demo.load(update_interface, None, [image_display, textbox, status, progress_bar])
+
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio
+datasets
+pillow