Update README.md
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README.md
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@@ -13,14 +13,14 @@ library_name: ultralytics
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### Anzhc's Face segmentation:
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#### Universal:
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Series of models aiming at detecting and segmenting face accurately. Trained on closed dataset i annotated myself.
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| Model | Target | mAP 50 | mAP 50-95 |Classes |Training Resolution|
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| --------------------------- | --------------------- | ----------------------------- | -------------------------
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| Anzhc Face -seg.pt | Face: illustration, real | LOST DATA | LOST DATA |2(male, female)| 640|
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| Anzhc Face -seg-hd.pt | Face: illustration, real | LOST DATA | LOST DATA |2(male, female)|1024|
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| Anzhc Face seg 640 v2 y8n.pt | Face: illustration, real | 0.872(box),0.872(mask) | 0.835(box),0.752(mask)|1(face) | 640|
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| Anzhc Face seg 768 v2 y8n.pt | Face: illustration, real | 0.86(box),0.86(mask) | 0.81(box),0.726(mask) |1(face) | 768|
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| Anzhc Face seg 768MS v2 y8n.pt | Face: illustration, real | 0.866(box),0.866(mask) | 0.816(box),0.72(mask) |1(face) | 768|(Multi-scale)|
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| Anzhc Face seg 1024 v2 y8n.pt | Face: illustration, real | 0.872(box),0.872(mask) | 0.804(box),0.726(mask)|1(face) | 1024|
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Take those stats with a grain of salt, since im pretty sure i re-scrambled dataset partition after training those models ages ago.
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Benchmark was performed in 640px.
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@@ -32,10 +32,10 @@ Difference in v2 models are only in their target resolution, so their performanc
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#### Real Face, gendered:
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Trained only on real photos for the most part, so will perform poorly with illustrations, but is gendered, and can be used for male/female detection stack.
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| Model | Target | mAP 50 | mAP 50-95 |Classes |Training Resolution|
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| --------------------------- | --------------------- | ----------------------------- | -------------------------
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| Anzhcs ManFace v02 1024 y8n.pt | Face: real | 0.883(box),0.883(mask) | 0.778(box), 0.704(mask) |1(face)|1024|
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| Anzhcs WomanFace v05 1024 y8n.pt | Face: real | 0.82(box),0.82(mask) | 0.713(box), 0.659(mask) |1(face)|1024|
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Benchmark was performed in 640px.
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### Anzhc's Face segmentation:
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| 14 |
#### Universal:
|
| 15 |
Series of models aiming at detecting and segmenting face accurately. Trained on closed dataset i annotated myself.
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| 16 |
+
| Model | Target | mAP 50 | mAP 50-95 |Classes |Dataset size|Training Resolution|
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+
| --------------------------- | --------------------- | ----------------------------- | ------------------------- |---------------|------------|-------------------|
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+
| Anzhc Face -seg.pt | Face: illustration, real | LOST DATA | LOST DATA |2(male, female)|LOST DATA| 640|
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+
| Anzhc Face -seg-hd.pt | Face: illustration, real | LOST DATA | LOST DATA |2(male, female)|LOST DATA|1024|
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+
| Anzhc Face seg 640 v2 y8n.pt | Face: illustration, real | 0.872(box),0.872(mask) | 0.835(box),0.752(mask)|1(face) |~500| 640|
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| Anzhc Face seg 768 v2 y8n.pt | Face: illustration, real | 0.86(box),0.86(mask) | 0.81(box),0.726(mask) |1(face) |~500| 768|
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| Anzhc Face seg 768MS v2 y8n.pt | Face: illustration, real | 0.866(box),0.866(mask) | 0.816(box),0.72(mask) |1(face) |~500| 768|(Multi-scale)|
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| Anzhc Face seg 1024 v2 y8n.pt | Face: illustration, real | 0.872(box),0.872(mask) | 0.804(box),0.726(mask)|1(face) |~500| 1024|
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| 24 |
|
| 25 |
Take those stats with a grain of salt, since im pretty sure i re-scrambled dataset partition after training those models ages ago.
|
| 26 |
Benchmark was performed in 640px.
|
|
|
|
| 32 |
#### Real Face, gendered:
|
| 33 |
Trained only on real photos for the most part, so will perform poorly with illustrations, but is gendered, and can be used for male/female detection stack.
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| 34 |
|
| 35 |
+
| Model | Target | mAP 50 | mAP 50-95 |Classes |Dataset size|Training Resolution|
|
| 36 |
+
| --------------------------- | --------------------- | ----------------------------- | ------------------------- |---------------|------------|-------------------|
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| 37 |
+
| Anzhcs ManFace v02 1024 y8n.pt | Face: real | 0.883(box),0.883(mask) | 0.778(box), 0.704(mask) |1(face)|~340|1024|
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| 38 |
+
| Anzhcs WomanFace v05 1024 y8n.pt | Face: real | 0.82(box),0.82(mask) | 0.713(box), 0.659(mask) |1(face) |~600|1024|
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Benchmark was performed in 640px.
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