Spaces:
Running on Zero
Running on Zero
File size: 4,142 Bytes
2407511 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 | {
"project": "SatQuery AI",
"team": "CodeBlueX",
"competition": "Smart India Hackathon 2026",
"problem_statement_id": "26167",
"organization": "ISRO / Department of Space",
"model_repository": "AnirudhShashikumar/SatQuery_AI_Models",
"repository_visibility": "private",
"public_upstream_dependencies": [
{
"name": "OpenCLIP ViT-L-14 laion2b_s32b_b82k",
"repository": "laion/CLIP-ViT-L-14-laion2B-s32B-b82K",
"revision": "1627032197142fbe2a7cfec626f4ced3ae60d07a",
"artifact": "open_clip_pytorch_model.safetensors",
"visibility": "public",
"codebluex_trained": false,
"used_by": "SatQuery Vision Encoder v1 reconstruction"
},
{
"name": "BLIP image-captioning base RSICD fine-tune",
"repository": "Gurveer05/blip-image-captioning-base-rscid-finetuned",
"revision": "57c4f0ff06264d374131637ce7c1e8dea079d589",
"visibility": "public",
"codebluex_trained": false,
"used_by": "RSICD captioner"
}
],
"codebluex_artifacts": [
{
"name": "SatQuery Vision Encoder v1 Adapter",
"path": "satquery_vision_encoder_v1/satquery_vision_encoder_v1_adapter.pt",
"sha256": "a99c0bf0fb44044988ef1698483888c8a2e3a047d2d2d56478837575cf7626ea",
"provenance": "CodeBlueX remote-sensing adaptation",
"base_architecture": "OpenCLIP ViT-L/14"
},
{
"name": "RSVQA Specialist v1 Head",
"path": "rsvqa_specialist_v1/rsvqa_specialist_v1_head.pt",
"sha256": "71c0ab56ee650813bd495e8a3bc777353b6907a097af860e417f60523efe56ad",
"provenance": "CodeBlueX trained/adapted specialist head",
"benchmark": {
"dataset": "RSVQA-LR official test split",
"samples": 10004,
"exact_accuracy_percent": 71.05,
"overflow_aware_accuracy_percent": 74.31
}
},
{
"name": "Grounding Specialist v1.1 Head",
"path": "grounding_specialist_v1_1/grounding_specialist_v1_1_head.pt",
"sha256": "5e8db30becadb1d063fc0154614ee2a2a4b7a2c2923db3fce4ff036c65007342",
"provenance": "CodeBlueX trained/adapted grounding specialist head",
"benchmark": {
"dataset": "VRSBench validation",
"samples": 16146,
"miou": 0.2348,
"accuracy_at_0_50_percent": 25.05
}
},
{
"name": "Pix2Pix SAR Reconstruction Checkpoint",
"path": "sar_translation/pix2pix/pix2pix_gen_180.pth",
"local_path": "../pix2pix_gen_180.pth",
"sha256": "5bdc6bf9b29986860d6537265280bb47b74f85ebe1222256ddc59acce3a743b3",
"provenance": "CodeBlueX SatQuery SAR reconstruction pipeline",
"architecture": "Pix2Pix"
},
{
"name": "SARFusionFormer SAR Reconstruction Checkpoint",
"path": "sar_translation/sarfusionformer/sarfusionformer_256_decoder_best.pt",
"local_path": "../models/checkpoints/sarfusionformer_256_decoder_best.pt",
"sha256": "6c8ac2d482b66877a910a9c95e6398f9e0586f13f786d0243c736a2d10b30548",
"provenance": "CodeBlueX SatQuery SAR reconstruction pipeline",
"architecture": "SARFusionFormer"
},
{
"name": "SARFusionFormer Color Corrector",
"path": "sar_translation/sarfusionformer/color_corrector_256_best.pt",
"local_path": "../models/checkpoints/color_corrector_256_best.pt",
"sha256": "15298976fbffe93c16d81716c40fe3c7a09499e63e649edd4de9a1fd70ec675d",
"provenance": "CodeBlueX SatQuery SAR reconstruction pipeline",
"architecture": "ColorCorrectionNet"
}
],
"third_party_components": [
{
"name": "Grounding DINO Tiny",
"local_path": "models/grounding_dino_tiny/model.safetensors",
"sha256": "1a2412ef99bd74bcd3c2a246fa1e48581f8889a1300c9051974741314fc042f3",
"provenance": "Third-party pretrained base model",
"codebluex_trained": false
},
{
"name": "ChangerEx",
"local_path": "models/changerex/ChangerEx_r18-512x512_40k_levircd_20221223_120511.pth",
"sha256": "da3f569306dadd1fac5b64abc2a3d484571cd0ecf6410e1f152275cfe49a3618",
"provenance": "Third-party pretrained checkpoint",
"codebluex_trained": false
}
]
}
|