turhancan97/visbench-detection-dinov2_vitb14

detection probe for dinov2_vitb14

A trained probe head, not a backbone. It is the small module VisBench fits on top of frozen dinov2_vitb14 features to measure what those features carry.

import visbench
from visbench.hub import load_probe_from_hub

backbone = visbench.get_backbone("dinov2_vitb14")
probe = load_probe_from_hub("turhancan97/visbench-detection-dinov2_vitb14", backbone=backbone)

It only works with this backbone

These weights were fitted on features from dinov2_vitb14, taken with pooling=mean and feature_mode=dense_only. Loading them against anything else is refused, because the failure is otherwise silent: a head fitted on one pooling and fed another has the right shapes and produces a plausible, wrong number.

backbone	dinov2_vitb14
backbone key	dinov2/dinov2_vitb14/224/7764ea0f912e
task	detection (high_level)
pooling	mean (requested mean)
feature mode	dense_only
layers	None

Reported scores

metric	value
classes_scored	20.0000
detections_per_image	88.5717
map_50	0.2897
map_50_95	0.0988

Reproducing it

Fitted with:

• batch_size: 8
• box_weight: 2.0
• epochs: 10
• focal_alpha: 0.25
• focal_gamma: 2.0
• head: detection
• hidden_dim: 0
• image_size: 224
• iou_thresholds: [0.5, 0.55, 0.6, 0.65, 0.7, 0.75, 0.8, 0.85, 0.9, 0.95]
• lr: 0.0005
• max_detections: 100
• nms_iou: 0.5
• num_classes: 20
• optimizer: adamw
• protocol: visbench_anchor_free_det
• score_threshold: 0.05
• warmup_epochs: 1.5
• weight_decay: 0.0001

Generated by VisBench.