feat: initial commit

.gitignore

@@ -0,0 +1,6 @@
+.DS_Store
+yolo*.pt
+# __pycache__
+gradio_queue.db
+__pycache__
+.venv

README.md

@@ -1,5 +1,5 @@
 ---
-title: Yolov11x Codh Char
+title: Yolov11x Char
 emoji: 👁
 colorFrom: pink
 colorTo: green

app.py

@@ -0,0 +1,113 @@
+import gradio as gr
+import json
+from PIL import Image, ImageDraw
+from ultralytics import YOLO
+
+# Model Heading and Description
+model_heading = "YOLOv11x Character"
+description = """YOLOv11x Character Gradio demo for object detection. Upload an image or click an example image to use."""
+
+article = "<p style='text-align: center'>YOLOv11x Character is an object detection model trained on the <a href=\"http://codh.rois.ac.jp/char-shape/\">日本古典籍くずし字データセット</a>.</p>"
+
+image_path= [
+       
+    ['『源氏物語』(東京大学総合図書館所蔵).jpg', 0.25, 0.45],
+    ['『源氏物語』(京都大学所蔵).jpg', 0.25, 0.45],
+    ['『平家物語』(国文学研究資料館提供).jpg', 0.25, 0.45]
+]
+
+# Load YOLO model
+model = YOLO('best.pt')
+
+
+def get_color(score):
+    """Returns color based on confidence score."""
+    if score > 0.75:
+        return "blue"       # 高スコアに濃い青
+    elif score > 0.5:
+        return "deepskyblue"  # 中スコアに明るい青
+    elif score > 0.25:
+        return "lightblue"  # 低スコアに薄い青
+    else:
+        return "gray"       # 非常に低いスコアにグレー
+
+def draw_boxes(image_path, results):
+    # Open image
+    image = Image.open(image_path)
+    draw = ImageDraw.Draw(image)
+
+    # 画像の短辺に基づいて矩形の線の太さを調整
+    min_dimension = min(image.size)  # 画像の短辺を取得
+    line_width = max(1, min_dimension // 200)  # 線の太さを短辺の1%程度に設定（最小値は1）
+    
+    # Draw boxes
+    for item in results:
+        box = item['box']
+        # label = item['class']
+        score = item['confidence']
+        
+        # Define box coordinates
+        x1, y1, x2, y2 = box["x1"], box["y1"], box["x2"], box["y2"]
+
+        color = get_color(score)
+        
+        # Draw rectangle and label
+        draw.rectangle([x1, y1, x2, y2], outline=color, width=line_width)
+        # draw.text((x1, y1), f"{label} {score:.2f}", fill=color)
+    
+    return image
+
+def YOLOv11x_img_inference(
+    image: gr.Image = None,
+    conf_threshold: gr.Slider = 0.25,
+    iou_threshold: gr.Slider = 0.45,
+):
+    """
+    YOLOv11x inference function
+    Args:
+        image: Input image
+        conf_threshold: Confidence threshold
+        iou_threshold: IOU threshold
+    Returns:
+        Rendered image
+        JSON output
+    """
+    results = model.predict(image, conf=conf_threshold, iou=iou_threshold, device="cpu")          
+
+    json_data = json.loads(results[0].tojson())
+
+    # Draw boxes on image
+    result_image = draw_boxes(image, json_data)
+    
+    return result_image, json_data
+
+    
+inputs_image = [
+    gr.Image(type="filepath", label="Input Image"),
+    gr.Slider(minimum=0.0, maximum=1.0, value=0.25, step=0.05, label="Confidence Threshold"),
+    gr.Slider(minimum=0.0, maximum=1.0, value=0.45, step=0.05, label="IOU Threshold"),
+]
+
+outputs_image =[
+    gr.Image(type="filepath", label="Output Image"),
+    gr.JSON(label="Output JSON")
+]
+demo = gr.Interface(
+    fn=YOLOv11x_img_inference,
+    inputs=inputs_image,
+    outputs=outputs_image,
+    title=model_heading,
+    description=description,
+    examples=image_path,
+    article=article,
+    cache_examples=False
+)
+
+demo.css = """
+.json-holder {
+    height: 300px;
+    overflow: auto;
+}
+"""
+
+demo.launch(share=False)

best.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cdff382908ed02720c5f80a3f519d9273ad3e5e01abba80b4b484f455f34c988
+size 114391826

init.sh

@@ -0,0 +1,5 @@
+wget https://iiif.dl.itc.u-tokyo.ac.jp/iiif/genji/TIFF/A00_6587/01/01_0004.tif/full/1024,/0/default.jpg -O "『源氏物語』(東京大学総合図書館所蔵).jpg"
+
+wget https://rmda.kulib.kyoto-u.ac.jp/iiif/RB00007030/01/RB00007030_00003_0.ptif/full/1024,/0/default.jpg -O "『源氏物語』(京都大学所蔵).jpg"
+
+wget https://kotenseki.nijl.ac.jp/api/iiif/100312034/v4/HRSM/HRSM-00396/HRSM-00396-00012.tif/full/1024,/0/default.jpg -O "『平家物語』(国文学研究資料館提供).jpg"

requirements-dev.txt

@@ -0,0 +1,3 @@
+# --upgrade pip
+-r requirements.txt
+gradio

requirements.txt

@@ -0,0 +1,2 @@
+ultralytics
+Pillow