yolov8-face-bengali-video

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 → 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

Evaluation Results

Usage

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)

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