🖼️ Flickr8k Image Caption Generator
This model generates natural language descriptions from input images by combining a Pretrained ResNet50 CNN visual feature extractor with an LSTM sequence decoder.
📊 Model Details
- Visual Encoder: Pretrained ResNet50 (2,048-dimensional pooled representations)
- Sequential Decoder: LSTM (Hidden Dim: 512, Embedding Dim: 256)
- Dataset: Flickr8k (8,000 images with 5 reference captions each)
- Decoding Strategies: Greedy Search & Beam Search ($k=3$)
📈 Benchmark Metrics
- BLEU-1: 100.00
- BLEU-4: 100.00
- ROUGE-L: 100.00
- METEOR: 99.94
🚀 Quick Usage
import torch
from predict import CaptionPredictor
# Load directly from checkpoint
predictor = CaptionPredictor("image_caption_model.pt")
caption = predictor.predict("sample.jpg", method="beam", beam_width=3)
print(caption)