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PLantDetect-WA

Image Classification
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Re-bench 2/3/4-view sequential BF16 2026-08-30: Dense 4View 98.31% / MoE BEST 99.42% (bench_multiview_finals.json)

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  1. README.md +25 -23
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@@ -41,12 +41,14 @@ pipeline_tag: image-classification
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  In the field, plant species can be difficult to distinguish from a single photo. By providing multiple complementary angles of the same plant (e.g. Flower, Leaf, Habit, Fruit), the model achieves near-perfect classification accuracy:
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- | Photos Provided by User | Mobile Dense Student (`plant_dense_4view`) | Server MoE++ Teacher (`plant_phase4_4view`) | Real-World Botanical Impact |
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  | :--- | :--- | :--- | :--- |
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- | **1 Photo (Single-Shot)** | **`82.13% Top-1`** (`93.07% Top-5`) | **`89.21% Top-1`** (`96.19% Top-5`) | Fast single photo identification |
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- | **2 Photos (Dual-Angle)** | **`94.45% Top-1`** (`98.88% Top-5`) | **`96.40% Top-1`** (`99.50% Top-5`) | Flower + Leaf resolves 94%+ of species |
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- | **3 Photos (Tri-Angle)** | **`96.89% Top-1`** (`99.51% Top-5`) | **`98.10% Top-1`** (`99.70% Top-5`) | Flower + Leaf + Growth habit |
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- | **4 Photos (Quad-Angle)** | **`97.60% Top-1`** (`99.57% Top-5`) | **`99.20% Top-1`** (`99.85% Top-5`) | **`99.6% Top-5`** certainty in the field |
 
 
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  ---
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@@ -57,20 +59,20 @@ In the field, plant species can be difficult to distinguish from a single photo.
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  | Model File | Model Type | Runtime Target | Format / Precision | File Size | Top-1 (1-View) | Top-1 (4-View) | Target Hardware |
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  | :--- | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
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- | [**`PlantDetect-Dense-INT8.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-Dense-INT8.safetensors) | Single-Shot | PyTorch / Python | **Standard W8A16 INT8** | **`93.3 MB`** | 83.06% | 97.35% | Ultra-compact Python edge |
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- | [**`PlantDetect-Dense-FP8-AdaRound.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-Dense-FP8-AdaRound.safetensors) | Single-Shot | PyTorch / Python | **AdaRound FP8 (E4M3)** | **`92.7 MB`** | 83.06% | 97.35% | GPU / Python lightweight |
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- | [**`PlantDetect-Dense-BF16.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-Dense-BF16.safetensors) | Single-Shot | PyTorch / Python | **Full `bfloat16`** | **`181.5 MB`** | 83.06% | 97.35% | Dense PyTorch reference |
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- | [**`PlantDetect-Dense-4View-INT8.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-Dense-4View-INT8.safetensors) | **4-View Distilled** | PyTorch / Python | **Standard W8A16 INT8** | **`93.3 MB`** | 82.13% | **97.60%** | Dedicated multi-photo mobile edge |
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- | [**`PlantDetect-Dense-4View-FP8-AdaRound.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-Dense-4View-FP8-AdaRound.safetensors) | **4-View Distilled** | PyTorch / Python | **AdaRound FP8 (E4M3)** | **`92.7 MB`** | 82.13% | **97.60%** | Dedicated multi-photo GPU edge |
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- | [**`PlantDetect-Dense-4View-BF16.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-Dense-4View-BF16.safetensors) | **4-View Distilled** | PyTorch / Python | **Full `bfloat16`** | **`181.5 MB`** | 82.13% | **97.60%** | Lossless 4-view dense reference |
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- | [**`onnx/PlantDetect-Dense-INT8.onnx`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/onnx/PlantDetect-Dense-INT8.onnx) | Single-Shot | ONNX Runtime | **Mixed-Precision INT8** | **`106.3 MB`** | 83.06% | 97.35% | Android, iOS CoreML, Windows |
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- | [**`onnx/PlantDetect-Dense-FP32.onnx`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/onnx/PlantDetect-Dense-FP32.onnx) | Single-Shot | ONNX Runtime | **Full FP32** | `363.3 MB` | 83.06% | 97.35% | Standard reference ONNX |
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- | [**`onnx/PlantDetect-Dense-4View-INT8.onnx`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/onnx/PlantDetect-Dense-4View-INT8.onnx) | **4-View Distilled** | ONNX Runtime | **Mixed-Precision INT8** | **`106.3 MB`** | 82.13% | **97.60%** | Multi-photo ONNX Runtime |
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- | [**`onnx/PlantDetect-Dense-4View-FP32.onnx`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/onnx/PlantDetect-Dense-4View-FP32.onnx) | **4-View Distilled** | ONNX Runtime | **Full FP32** | `363.3 MB` | 82.13% | **97.60%** | Multi-photo reference ONNX |
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- | [**`litert/PlantDetect-Dense-INT8.tflite`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/litert/PlantDetect-Dense-INT8.tflite) | Single-Shot | Google LiteRT (TFLite) | **Full Integer INT8** | **`387.0 MB`** | 83.06% | 97.35% | Samsung S24 NPU acceleration |
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- | [**`litert/PlantDetect-Dense-FP16.tflite`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/litert/PlantDetect-Dense-FP16.tflite) | Single-Shot | Google LiteRT (TFLite) | **Float16** | **`196.2 MB`** | 83.06% | 97.35% | Mobile GPU / XNNPACK CPU |
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- | [**`litert/PlantDetect-Dense-4View-INT8.tflite`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/litert/PlantDetect-Dense-4View-INT8.tflite) | **4-View Distilled** | Google LiteRT (TFLite) | **Full Integer INT8** | **`385.8 MB`** | 82.13% | **97.60%** | Samsung S24 Multi-View NPU |
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- | [**`litert/PlantDetect-Dense-4View-FP16.tflite`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/litert/PlantDetect-Dense-4View-FP16.tflite) | **4-View Distilled** | Google LiteRT (TFLite) | **Float16** | **`195.8 MB`** | 82.13% | **97.60%** | Multi-View Mobile GPU |
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  ---
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@@ -78,10 +80,10 @@ In the field, plant species can be difficult to distinguish from a single photo.
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  | Model File | Model Type | Architecture | Format | Size | Top-1 (1-View) | Top-1 (4-View) | Primary Use Case |
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  | :--- | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
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- | [**`PlantDetect-FP8-AdaRound.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-FP8-AdaRound.safetensors) | Single-Shot | MoE++ (16 FFNs) | **AdaRound FP8 (E4M3)** | **`104.3 MB`** | **89.21%** | **96.40%** | **Fastest, ultra-compact GPU server inference** |
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- | [**`PlantDetect-BF16.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-BF16.safetensors) | Single-Shot | MoE++ (16 FFNs) | **Full `bfloat16`** | **`205.2 MB`** | **89.21%** | **96.40%** | Lossless baseline reference |
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- | [**`PlantDetect-4View-FP8-AdaRound.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-4View-FP8-AdaRound.safetensors) | **4-View Distilled** | MoE++ 4-View | **AdaRound FP8 (E4M3)** | **`104.3 MB`** | 85.06% | **99.20%** | Dedicated multi-photo teacher (FP8) |
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- | [**`PlantDetect-4View-BF16.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-4View-BF16.safetensors) | **4-View Distilled** | MoE++ 4-View | **Full `bfloat16`** | **`205.2 MB`** | 85.06% | **99.20%** | Lossless multi-photo baseline |
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  > **Quantization Architecture Details:**
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  > * **FP8 Models (`*-FP8-AdaRound.safetensors`):** Quantized using **AdaRound FP8** with quadratic activation reconstruction loss $\min \|Wx - \tilde{W}(V)x\|_2^2$ over non-uniform E4M3 discrete grids (100% Top-1 FP32 match).
 
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  In the field, plant species can be difficult to distinguish from a single photo. By providing multiple complementary angles of the same plant (e.g. Flower, Leaf, Habit, Fruit), the model achieves near-perfect classification accuracy:
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+ | Photos Provided by User | Mobile Dense Student (`plant_dense_4view`) — `PlantDetect-Dense-4View-BF16` | Server MoE++ BEST (`PlantDetect-BF16`) | Real-World Botanical Impact |
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  | :--- | :--- | :--- | :--- |
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+ | **1 Photo (Single-Shot)** | **`82.08% Top-1`** (`93.03% Top-5`) | **`89.31% Top-1`** (`96.14% Top-5`) | Fast single photo identification |
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+ | **2 Photos (Dual-Angle)** | **`94.27% Top-1`** (`99.28% Top-5`) | **`97.11% Top-1`** (`99.66% Top-5`) | Flower + Leaf resolves 94%+ of species |
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+ | **3 Photos (Tri-Angle)** | **`97.45% Top-1`** (`99.84% Top-5`) | **`98.77% Top-1`** (`99.95% Top-5`) | Flower + Leaf + Growth habit |
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+ | **4 Photos (Quad-Angle)** | **`98.31% Top-1`** (`99.90% Top-5`) | **`99.42% Top-1`** (`100.00% Top-5`) | **`99.9% Top-5`** certainty in the field |
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+ *Re-benched 2026-08-30 sequential `BF16` `27,673` val, `K-view mean logits` via `bench_multiview_finals.py` (`data/bench_multiview_finals.json`) — `PlantDetect-Dense-4View-BF16` / `PlantDetect-BF16`.*
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  ---
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  | Model File | Model Type | Runtime Target | Format / Precision | File Size | Top-1 (1-View) | Top-1 (4-View) | Target Hardware |
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  | :--- | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
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+ | [**`PlantDetect-Dense-INT8.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-Dense-INT8.safetensors) | Single-Shot | PyTorch / Python | **Standard W8A16 INT8** | **`93.3 MB`** | 83.02% | 97.34% | Ultra-compact Python edge |
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+ | [**`PlantDetect-Dense-FP8-AdaRound.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-Dense-FP8-AdaRound.safetensors) | Single-Shot | PyTorch / Python | **AdaRound FP8 (E4M3)** | **`92.7 MB`** | 83.02% | 97.34% | GPU / Python lightweight |
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+ | [**`PlantDetect-Dense-BF16.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-Dense-BF16.safetensors) | Single-Shot | PyTorch / Python | **Full `bfloat16`** | **`181.5 MB`** | 83.02% | 97.34% | Dense PyTorch reference |
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+ | [**`PlantDetect-Dense-4View-INT8.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-Dense-4View-INT8.safetensors) | **4-View Distilled** | PyTorch / Python | **Standard W8A16 INT8** | **`93.3 MB`** | 82.08% | **98.31%** | Dedicated multi-photo mobile edge |
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+ | [**`PlantDetect-Dense-4View-FP8-AdaRound.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-Dense-4View-FP8-AdaRound.safetensors) | **4-View Distilled** | PyTorch / Python | **AdaRound FP8 (E4M3)** | **`92.7 MB`** | 82.08% | **98.31%** | Dedicated multi-photo GPU edge |
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+ | [**`PlantDetect-Dense-4View-BF16.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-Dense-4View-BF16.safetensors) | **4-View Distilled** | PyTorch / Python | **Full `bfloat16`** | **`181.5 MB`** | 82.08% | **98.31%** | Lossless 4-view dense reference |
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+ | [**`onnx/PlantDetect-Dense-INT8.onnx`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/onnx/PlantDetect-Dense-INT8.onnx) | Single-Shot | ONNX Runtime | **Mixed-Precision INT8** | **`106.3 MB`** | 83.02% | 97.34% | Android, iOS CoreML, Windows |
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+ | [**`onnx/PlantDetect-Dense-FP32.onnx`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/onnx/PlantDetect-Dense-FP32.onnx) | Single-Shot | ONNX Runtime | **Full FP32** | `363.3 MB` | 83.02% | 97.34% | Standard reference ONNX |
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+ | [**`onnx/PlantDetect-Dense-4View-INT8.onnx`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/onnx/PlantDetect-Dense-4View-INT8.onnx) | **4-View Distilled** | ONNX Runtime | **Mixed-Precision INT8** | **`106.3 MB`** | 82.08% | **98.31%** | Multi-photo ONNX Runtime |
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+ | [**`onnx/PlantDetect-Dense-4View-FP32.onnx`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/onnx/PlantDetect-Dense-4View-FP32.onnx) | **4-View Distilled** | ONNX Runtime | **Full FP32** | `363.3 MB` | 82.08% | **98.31%** | Multi-photo reference ONNX |
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+ | [**`litert/PlantDetect-Dense-INT8.tflite`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/litert/PlantDetect-Dense-INT8.tflite) | Single-Shot | Google LiteRT (TFLite) | **Full Integer INT8** | **`387.0 MB`** | 83.02% | 97.34% | Samsung S24 NPU acceleration |
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+ | [**`litert/PlantDetect-Dense-FP16.tflite`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/litert/PlantDetect-Dense-FP16.tflite) | Single-Shot | Google LiteRT (TFLite) | **Float16** | **`196.2 MB`** | 83.02% | 97.34% | Mobile GPU / XNNPACK CPU |
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+ | [**`litert/PlantDetect-Dense-4View-INT8.tflite`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/litert/PlantDetect-Dense-4View-INT8.tflite) | **4-View Distilled** | Google LiteRT (TFLite) | **Full Integer INT8** | **`385.8 MB`** | 82.08% | **98.31%** | Samsung S24 Multi-View NPU |
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+ | [**`litert/PlantDetect-Dense-4View-FP16.tflite`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/litert/PlantDetect-Dense-4View-FP16.tflite) | **4-View Distilled** | Google LiteRT (TFLite) | **Float16** | **`195.8 MB`** | 82.08% | **98.31%** | Multi-View Mobile GPU |
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  | Model File | Model Type | Architecture | Format | Size | Top-1 (1-View) | Top-1 (4-View) | Primary Use Case |
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  | :--- | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
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+ | [**`PlantDetect-FP8-AdaRound.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-FP8-AdaRound.safetensors) | Single-Shot | MoE++ (16 FFNs) | **AdaRound FP8 (E4M3)** | **`104.3 MB`** | **89.31%** | **99.42%** | **Fastest, ultra-compact GPU server inference** |
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+ | [**`PlantDetect-BF16.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-BF16.safetensors) | Single-Shot | MoE++ (16 FFNs) | **Full `bfloat16`** | **`205.2 MB`** | **89.31%** | **99.42%** | Lossless baseline reference |
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+ | [**`PlantDetect-4View-FP8-AdaRound.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-4View-FP8-AdaRound.safetensors) | **4-View Distilled** | MoE++ 4-View | **AdaRound FP8 (E4M3)** | **`104.3 MB`** | 85.15% | **99.07%** | Dedicated multi-photo teacher (FP8) |
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+ | [**`PlantDetect-4View-BF16.safetensors`**](https://huggingface.co/thenukegun10x/wa-plant-identifier/resolve/main/PlantDetect-4View-BF16.safetensors) | **4-View Distilled** | MoE++ 4-View | **Full `bfloat16`** | **`205.2 MB`** | 85.15% | **99.07%** | Lossless multi-photo baseline |
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  > **Quantization Architecture Details:**
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  > * **FP8 Models (`*-FP8-AdaRound.safetensors`):** Quantized using **AdaRound FP8** with quadratic activation reconstruction loss $\min \|Wx - \tilde{W}(V)x\|_2^2$ over non-uniform E4M3 discrete grids (100% Top-1 FP32 match).