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models.json

@@ -3,458 +3,248 @@
   "updated_at": "2026-04-10",
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+      "upstream": { "name": "microsoft/MoGe", "url": "https://github.com/microsoft/MoGe", "year": 2025 }
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+      "description_md": "Zero-shot image classification. Dual encoder (image + text) with sigmoid loss. 224×224 input. Type any class names to classify.",
       "demo": {
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         "config": {
@@ -469,50 +259,40 @@
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-        "name": "google-research/big_vision",
-        "url": "https://github.com/google-research/big_vision",
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+      "license": { "name": "Apache-2.0", "url": "https://github.com/google-research/big_vision" },
+      "upstream": { "name": "google-research/big_vision", "url": "https://github.com/google-research/big_vision", "year": 2023 }
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       "subtitle": "Microsoft, 2024",
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@@ -523,132 +303,83 @@
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+      "name": "AdaFace",
+      "subtitle": "Face Recognition, 2022",
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+      "description_md": "Face recognition via 512-dim embeddings. IR-18 backbone, 112×112 face crop input. Compare faces by cosine similarity.",
       "demo": {
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-        "config": {
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+        "template": "face_compare",
+        "config": { "input_size": 112, "embedding_dim": 512, "match_threshold": 0.6 }
       },
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+          "name": "AdaFace_IR18_CASIA.mlpackage.zip",
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+      "license": { "name": "MIT", "url": "https://github.com/mk-minchul/AdaFace" },
+      "upstream": { "name": "mk-minchul/AdaFace", "url": "https://github.com/mk-minchul/AdaFace", "year": 2022 }
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       "category_id": "generation",
-      "description_md": "Single-step text-to-image from SD1.5 via TCD distillation. 512×512. Chunked UNet (6-bit).",
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+      "name": "Basic Pitch",
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       "category_id": "audio",
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+      "name": "Real-ESRGAN 4x",
+      "subtitle": "Super Resolution, 2021",
+      "category_id": "enhancement",
+      "description_md": "Real-world blind super-resolution. 4× upscale from any input. Handles noise, blur, and JPEG artifacts. 512×512 input → 2048×2048 output.",
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+        "config": { "input_size": 512, "output_type": "image" }
       },
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-        "url": "https://github.com/myshell-ai/OpenVoice"
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+      "upstream": { "name": "xinntao/Real-ESRGAN", "url": "https://github.com/xinntao/Real-ESRGAN", "year": 2021 }
+    },
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+      "name": "GFPGAN",
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+      "category_id": "restoration",
+      "description_md": "Blind face restoration with generative facial prior. Restores degraded face photos to high quality. 512×512 input/output.",
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-      "category_id": "audio",
-      "description_md": "Speaker diarization: who spoke when. 16 kHz mono, 10s segments.",
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+      "name": "RF-DETR Nano",
+      "subtitle": "Object Detection, 2025",
+      "category_id": "detection",
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+      "category_id": "segmentation",
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+        "config": { "input_size": 512, "output_type": "segmap", "num_classes": 19 }
+      },
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+      "category_id": "segmentation",
+      "description_md": "Lightweight Segment Anything. Tap any point to generate a segmentation mask. ViT-Tiny encoder (13 MB) + lightweight decoder (9.8 MB). ~60× smaller than SAM.",
+      "demo": {
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+          "decoder": "MobileSAM_Decoder.mlpackage.zip",
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+      "name": "LaMa",
+      "subtitle": "Image Inpainting, 2022",
+      "category_id": "inpainting",
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-        "url": "https://github.com/pyannote/pyannote-audio",
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+}