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conservationxlabs/
miewid-msv2

Name: miewid-msv2
Availability: InStock

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Model Details

Model Description

MiewID-msv2 is a feature extractor trained for re-identification using contrastive learning on a large, high-quality dataset of 54 wildlife species - terrestrial and aquatic - including fins, flukes, flanks, faces.

Model Type: Wildlife re-identification feature backbone
Model Stats:
- Params (M): 51.11
- GMACs: 24.38
- Activations (M): 91.11
- Image size: 440 x 440

Model Sources [optional]

Repository: https://github.com/WildMeOrg/wbia-plugin-miew-id
Backbone: https://huggingface.co/timm/efficientnetv2_rw_m.agc_in1k

Usage

Intended use is re-identification of individuals from different species by matching against a database of grount-truth samples. Model features can also be used for species classification by retrieval.

Embedding Extraction

import numpy as np
from PIL import Image
import torch
import torchvision.transforms as transforms
from transformers import AutoModel

model_tag = f"conservationxlabs/miewid-msv2"
model = AutoModel.from_pretrained(model_tag, trust_remote_code=True)

def generate_random_image(height=440, width=440, channels=3):
    random_image = np.random.randint(0, 256, (height, width, channels), dtype=np.uint8)
    return Image.fromarray(random_image)

random_image = generate_random_image()

preprocess = transforms.Compose([
    transforms.Resize((440, 440)),
    transforms.ToTensor(),
    transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
])

input_tensor = preprocess(random_image)
input_batch = input_tensor.unsqueeze(0) 

with torch.no_grad():
    output = model(input_batch)

print(output)
print(output.shape)

More Examples

View more usage examples at https://github.com/WildMeOrg/wbia-plugin-miew-id/tree/main/wbia_miew_id/examples

Training Details

Training Data

The dataset used for these experiments was a combination of data from Wildbook platforms (multiple users), Happywhale Kaggle competitions multi-species dataset and multiple publicly available datasets. A small subset of data from Wildbook platforms is available at https://lila.science/datasets.

Example images

Evaluation Results

The multi-species model shows improvements over models trained on single species. Moreover the model shows strong generalization ability for majority of the species when trained and evaluated in a leave-one-out fashion.

Detailed results

Source	group	map	rank-1	rank-5	rank-10	rank-20	viewpoints	n_test_annots	n_test_names	n_train_annots	n_train_names
Wildbook	amur_tiger	91.8	100.0	100.0	100.0	100.0	['left', 'right']	233	47	691	75
Wildbook	beluga_whale	61.36	71.85	81.63	85.51	89.28	['up']	849	228	2767	354
Happywhale	blue_whale	36.98	38.68	55.11	61.52	69.04	['unknown']	998	392	1185	339
Wildbook	bottlenose_dolphin	85.69	93.99	96.18	96.85	97.52	['right', 'left']	4911	838	11607	1062
Happywhale	brydes_whale	69.96	80.95	92.86	95.24	100.0	['unknown']	42	9	81	15
Lomas Capuchin	capuchin	34.8	47.97	68.58	76.69	85.14	['front']	296	35	1708	29
Wildbook	cheetah	57.37	71.15	84.92	87.87	92.13	['left', 'right']	624	139	1522	144
Wildbook	chimpanzee	94.7	100.0	100.0	100.0	100.0	['unknown']	52	8	138	9
C-Tai	chimpanzee_ctai	51.67	69.64	83.68	89.18	94.12	['front']	527	63	2680	44
C-Zoo	chimpanzee_czoo	77.66	86.67	93.33	97.5	99.17	['front']	240	24	1258	17
Happywhale	commersons_dolphin	0.0	0.0	0.0	0.0	0.0	['unknown']	10	5	7	2
Happywhale	cuviers_beaked_whale	52.89	55.71	75.71	82.86	90.0	['unknown']	70	28	89	21
DogFaceNet	dog	82.96	87.38	94.78	96.74	97.99	['unknown']	1838	544	5750	1088
Happywhale	dusky_dolphin	85.82	83.54	93.04	94.3	94.94	['unknown']	158	68	154	41
Wildbook	eurasianlynx	58.8	67.82	83.78	88.83	92.02	['left', 'right']	726	199	2251	285
Happywhale	fin_whale	67.65	76.92	87.18	90.11	93.04	['unknown']	273	71	533	55
Happywhale	frasiers_dolphin	0.0	0.0	0.0	0.0	0.0		-1	-1	-1	-1
Wildbook	giraffe	99.18	99.08	99.08	100.0	100.0	['right', 'front', 'left', 'back']	423	162	2540	426
Wildbook	horse_wild+face	0.0	0.0	0.0	0.0	0.0	['front']	17	7	174	53
Wildbook	horse_wild_tunisian+face	79.59	98.53	99.51	100.0	100.0	['unknown']	204	39	999	37
Wildbook	hyena	64.17	79.32	89.22	93.14	96.41	['right', 'left']	1231	301	1154	201
Wildbook	hyperoodon_ampullatus	91.14	96.11	98.12	98.34	98.84	['left', 'right']	1930	354	24952	759
Wildbook	jaguar	67.45	81.72	91.04	92.91	94.4	['left', 'right']	540	124	980	103
PrimFace	japanese_monkey	89.05	93.85	98.46	98.46	100.0	['unknown']	65	12	219	14
Happywhale	killer_whale	62.82	77.13	85.48	88.81	91.82	['unknown']	599	145	1379	177
Wildbook	leopard	65.03	82.64	90.23	92.83	94.46	['right', 'left']	595	108	4261	381
Wildbook	lion	87.12	93.86	100.0	100.0	100.0	['front', 'unknown', 'frontright', 'frontleft', 'upfront', 'right', 'upleft', 'left', 'upright', 'backleft', 'back']	1364	242	3981	241
Happywhale	long_finned_pilot_whale	99.06	98.11	100.0	100.0	100.0	['unknown']	53	21	33	10
Wildbook	lynx_pardinus	48.22	57.68	73.44	77.18	84.96	['left', 'right']	467	142	1376	259
MacaqueFaces	macaque_face	89.87	95.88	97.94	99.12	100.0	['front']	340	34	3480	25
Happywhale	melon_headed_whale	90.8	93.42	96.05	96.71	98.68	['unknown']	152	55	180	43
Wildbook	nyala	64.64	70.65	90.05	94.03	97.01	['left', 'right']	418	99	1303	149
Happywhale	pantropic_spotted_dolphin	78.15	85.19	90.74	94.44	96.3	['unknown']	54	11	55	8
Happywhale	pygmy_killer_whale	89.07	84.62	100.0	100.0	100.0	['unknown']	26	10	32	5
PrimFace	rhesus_monkey	78.12	89.13	97.28	98.91	100.0	['unknown']	184	28	478	24
Happywhale	rough_toothed_dolphin	0.0	0.0	0.0	0.0	0.0	['unknown']	6	3	7	2
SealID	seal	37.93	59.51	80.0	86.1	91.71	['unknown']	410	41	1448	36
Happywhale	sei_whale	67.86	71.55	87.07	93.1	95.69	['unknown']	116	35	106	29
Wildbook	short_fin_pilot_whale+fin_dorsal	92.49	92.31	98.08	100.0	100.0	['right', 'left']	272	64	1290	137
Happywhale	short_finned_pilot_whale	94.39	94.96	95.8	95.8	97.48	['unknown']	119	57	67	17
Wildbook	snow_leopard	62.43	82.45	88.91	92.15	94.53	['left', 'right']	927	144	2307	99
Happywhale	spinner_dolphin	99.88	100.0	100.0	100.0	100.0	['left', 'right']	335	97	1562	251
Happywhale	spotted_dolphin	84.92	83.67	89.8	95.92	97.96	['unknown']	49	22	128	28
Wildbook	turtle_green	100.0	100.0	100.0	100.0	100.0	['left', 'right', 'up', 'front']	543	109	5097	76
Wildbook	turtle_green+head	95.1	96.02	100.0	100.0	100.0	['left', 'right', 'up', 'front']	544	108	5737	76
Wildbook	turtle_hawksbill	78.84	81.15	88.37	92.56	95.81	['up', 'left', 'right', 'front']	506	106	5397	71
Wildbook	turtle_hawksbill+head	86.78	91.74	95.45	96.69	98.35	['right', 'left', 'up', 'front']	589	109	7033	71
SeaTurtleID	turtle_loggerhead_ext	63.67	75.43	86.61	90.17	92.87	['unknown', 'left', 'top', 'right']	815	217	6573	355
SeaTurtleID	turtle_loggerhead_ext+head	94.14	94.63	100.0	100.0	100.0	['left', 'right', 'topright', 'top', 'topleft', 'below', 'front']	778	209	6361	348
Wildbook	whale_fin+fin_dorsal	82.12	85.12	93.87	95.04	95.75	['left', 'right']	394	110	1629	186
Wildbook	whale_grey	90.97	91.55	95.54	96.18	96.82	['right', 'left']	381	103	5662	758
Wildbook	whale_humpback+fin_dorsal	80.3	84.07	90.08	91.6	95.42	['right', 'left']	509	194	3734	541
Wildbook	whale_humpback+fluke	97.11	96.67	100.0	100.0	100.0	['back']	150	64	1151	356
Wildbook	whale_orca	97.01	98.36	99.18	100.0	100.0	['right', 'left']	249	49	2790	435
Wildbook	whale_orca+fin_dorsal	95.41	95.87	97.52	97.52	99.17	['right', 'left']	623	187	3978	430
Wildbook	whale_sperm+fluke	96.14	97.87	98.33	98.48	99.09	['back']	658	125	25849	558
Wildbook	whaleshark	57.61	72.25	79.96	82.27	87.21	['left', 'right']	997	212	5713	376
Wildbook	white_shark+fin_dorsal	91.4	94.89	97.87	98.54	99.27	['left', 'right']	322	88	1067	162
Happywhale	white_sided_dolphin	81.82	76.0	88.0	88.0	100.0	['unknown']	25	11	13	4
Wildbook	wilddog	73.4	85.11	90.93	92.38	94.07	['left', 'right']	3460	848	4217	656
Wildbook	zebra_grevys	91.79	96.79	97.57	97.74	98.04	['right']	1684	332	8927	362