Mirror fork of Daniil-Domino/yolo11x-text-detection

.gitattributes

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README.md

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+---
+license: agpl-3.0
+datasets:
+- ai-forever/school_notebooks_RU
+language:
+- ru
+base_model:
+- Ultralytics/YOLO11
+library_name: ultralytics
+library_version: 8.3.155
+pipeline_tag: object-detection
+tags:
+- yolo
+- yolo11
+- yolo11x
+- htr
+- text-detection
+---
+
+# Handwritten Russian Text Detection using YOLO11
+
+YOLO11x was fine-tuned on the [School Notebooks Dataset](https://huggingface.co/datasets/ai-forever/school_notebooks_RU) and an additional dataset of over 30 images containing printed text.
+
+For more information, check out the [GitHub repository](https://github.com/DialecticalHTR/RuDialect-HTR).
+
+## Model description
+
+YOLO11x was fine-tuned for Handwritten Russian Text Detection in school notebooks.
+The model was trained for 100 epochs with a batch size of 16 using dual NVIDIA T4 GPUs. The fine-tuning process took approximately 93 minutes.
+
+# Example Usage
+
+```python
+# Load libraries
+import cv2
+from ultralytics import YOLO
+from pathlib import Path
+import matplotlib.pyplot as plt
+from huggingface_hub import hf_hub_download
+
+
+# Download model
+model_path = hf_hub_download(repo_id="Daniil-Domino/yolo11x-text-detection", filename="model.pt")
+
+# Load model
+model = YOLO(model_path)
+
+# Inference
+image_path = "/path/to/image"
+image = cv2.imread(image_path).copy()
+output = model.predict(image, conf=0.3)
+
+# Draw bounding boxes
+out_image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+for data in output[0].boxes.data.tolist():
+    xmin, ymin, xmax, ymax, _, _ = map(int, data)        
+    cv2.rectangle(out_image, (xmin, ymin), (xmax, ymax), color=(0, 0, 255), thickness=3)
+
+# Display result
+plt.figure(figsize=(15, 10))
+plt.imshow(out_image)
+plt.axis('off')
+plt.show()
+```
+
+# Metrics
+Below are the key evaluation metrics on the validation set:
+- **Precision**: 0.929
+- **Recall**: 0.937
+- **mAP50**: 0.966
+- **mAP50-95**: 0.725

model.pt

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+size 114390674

train/args.yaml

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+task: detect
+mode: train
+model: yolo11x.pt
+data: /kaggle/working/data.yaml
+epochs: 100
+time: null
+patience: 20
+batch: 16
+imgsz: 640
+save: true
+save_period: -1
+cache: false
+device:
+- 0
+- 1
+workers: 8
+project: null
+name: train
+exist_ok: true
+pretrained: true
+optimizer: AdamW
+verbose: true
+seed: 0
+deterministic: true
+single_cls: false
+rect: false
+cos_lr: true
+close_mosaic: 10
+resume: false
+amp: true
+fraction: 1.0
+profile: false
+freeze: null
+multi_scale: false
+overlap_mask: true
+mask_ratio: 4
+dropout: 0.1
+val: true
+split: val
+save_json: false
+conf: null
+iou: 0.7
+max_det: 300
+half: false
+dnn: false
+plots: true
+source: null
+vid_stride: 1
+stream_buffer: false
+visualize: false
+augment: false
+agnostic_nms: false
+classes: null
+retina_masks: false
+embed: null
+show: false
+save_frames: false
+save_txt: false
+save_conf: false
+save_crop: false
+show_labels: true
+show_conf: true
+show_boxes: true
+line_width: null
+format: torchscript
+keras: false
+optimize: false
+int8: false
+dynamic: false
+simplify: true
+opset: null
+workspace: null
+nms: false
+lr0: 1.0e-05
+lrf: 0.01
+momentum: 0.937
+weight_decay: 0.0005
+warmup_epochs: 3.0
+warmup_momentum: 0.8
+warmup_bias_lr: 0.1
+box: 7.5
+cls: 0.5
+dfl: 1.5
+pose: 12.0
+kobj: 1.0
+nbs: 64
+hsv_h: 0.015
+hsv_s: 0.7
+hsv_v: 0.4
+degrees: 0.0
+translate: 0.1
+scale: 0.5
+shear: 0.0
+perspective: 0.0
+flipud: 0.0
+fliplr: 0.5
+bgr: 0.0
+mosaic: 1.0
+mixup: 0.0
+copy_paste: 0.0
+copy_paste_mode: flip
+auto_augment: randaugment
+erasing: 0.4
+cfg: null
+tracker: botsort.yaml
+save_dir: runs/detect/train