---
language:
- bn
tags:
- object-detection
- face-detection
- yolov8
- ultralytics
- bengali-video
- caption-assignment
- wider-face
license: apache-2.0
datasets:
- lylmsc/wider-face-for-yolo-training
metrics:
- map
- precision
- recall
pipeline_tag: object-detection
base_model: ultralytics/yolov8n
---

# YOLOv8n Face Detection — Bengali Video Caption Pipeline

## Model Summary

Fine-tuned **YOLOv8n** for face/person detection in Bengali video frames.  
Part of a Bengali video auto-captioning system that combines:
- **This model** → detects visible faces in frames
- **[Tmanna/whisper-bengali-final](https://huggingface.co/Tmanna/whisper-bengali-final)** → Bengali speech-to-text
- **Rule-based visibility filter** → shows caption only when face is on screen

## Pipeline Architecture
```
Video
  ↓
Audio ──→ Whisper (Tmanna/whisper-bengali-final) ──→ Bengali caption text
  ↓
Frames ──→ THIS MODEL (YOLOv8 Face Detection)
  ↓
Visibility Filter (rule-based: len(boxes) > 0)
  ↓
IF face visible → overlay Bengali caption
ELSE            → skip caption for this frame
```

## Training Details

| Parameter     | Value |
|---------------|-------|
| Base Model    | `yolov8n.pt` (Ultralytics) |
| Dataset       | [lylmsc/wider-face-for-yolo-training](https://www.kaggle.com/datasets/lylmsc/wider-face-for-yolo-training) |
| Classes       | 1 (`face`) |
| Epochs        | 50 |
| Image Size    | 640 × 640 |
| Batch Size    | 32 |
| Hardware      | 2× NVIDIA T4 (Kaggle) |
| Optimizer     | AdamW + Cosine LR decay |
| Early Stop    | patience=10 |

## Evaluation Results

| Metric       | Score |
|--------------|-------|
| mAP@0.5      | 0.6994 |
| mAP@0.5:0.95 | 0.3665 |
| Precision    | 0.8556 |
| Recall       | 0.6104 |

## Usage
```python
from ultralytics import YOLO

model = YOLO("Tmanna/yolov8-face-bengali-video")

# On a video frame (numpy array or image path)
results = model("frame.jpg", conf=0.25)

faces = results[0].boxes
if len(faces) > 0:
    print("Face visible → show Bengali caption")
else:
    print("No face → skip caption")
```

## Visibility Filter (no extra model needed)
```python
def should_show_caption(frame_path, face_model, conf=0.25):
    results = face_model(frame_path, conf=conf, verbose=False)
    return len(results[0].boxes) > 0   # True = show, False = hide
```

## What This Model Does NOT Handle

| Module | Status | Reason |
|--------|--------|--------|
| Bengali STT | ✅ Handled by `Tmanna/whisper-bengali-final` | Pre-existing model |
| Translation | ❌ Not needed | English→Bengali not required |
| Speaker Diarization | ⚠️ Optional | Not in core pipeline |
| Face Tracking (DeepSORT) | ⚠️ Optional | Not in core pipeline |
| Active Speaker Detection | 🔴 Hard/Optional | Not in core pipeline |