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Model
Object Detection network to detect license plates in an image of a car.
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10 Versions
pruned_v2.2.1Signed
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09/20/2024 7:08 AM UTC1.7 MB
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pruned_v2.3.1Signed
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09/20/2024 7:08 AM UTC1.7 MB
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08/29/2024 5:59 PM UTC1.69 MBBatch Size: 1GPU: V100Copied!
08/29/2024 5:59 PM UTC1.69 MBBatch Size: 1GPU: V100
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SHA256 digests
| Key | Value |
|---|---|
| LPDNet_CCPD_pruned_tao5.onnx | 4b9b5937c8c4f72067f3f3d38889015790ab51b09b269c7a2e13f1885424f3cd |
| ccpd_cal_8.5.3.bin | f0a89bf9281deee75b4bc110dc36d3d59968a5ff87eaa4ecdfca1b557d074913 |
| LPDNet_usa_pruned_tao5.onnx | 8174ff09e316ec9fcc74ff0947bc73536a6f25a33aae1c52e9effab8a91c7930 |
| usa_cal_8.6.1.bin | 3c08a011e2307b036d69fbe163f2261855da4371607bbd88ffbe7df1a3b61562 |
| ccpd_cal_8.6.1.bin | 1e29c5740676caaf1c8968ecfc76c59f11872e2b7cd1d4d84f4e7c93c40ac865 |
| usa_cal_8.5.3.bin | d7e1ed384054496c5bfce67278604f40d2895b4000bd9012b5380e8f256cdb4c |
TAO Toolkit API
| Key | Value |
|---|---|
| endpoints | ['lpdnet'] |
| format_version | 0.0.1 |
| model_format | onnx |
| tao_version | ['>=5.5.0'] |
| trainable | False |
TAO Toolkit UI Metadata
| Key | Value |
|---|---|
| license | NVAIE EULA |
| is_backbone | False |
| task | lpdnet |
| format_version | 0.0.1 |
| backbone_type | cnn |
| domain | purpose-built |
| num_parameters | 169M |
| backbone_class | resnet |
11/07/2023 4:44 PM UTC1.69 MBAccuracy: 98120 EpochsBatch Size: 1GPU: V100
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pruned_v2.1Selected05/25/2022 3:40 PM UTC9.13 MBAccuracy: 98120 EpochsBatch Size: 1GPU: V100Copied!
pruned_v2.1Selected
05/25/2022 3:40 PM UTC9.13 MBAccuracy: 98120 EpochsBatch Size: 1GPU: V100
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1. MODEL OVERVIEW
| Key | Value |
|---|---|
| 2. Model Architecture | YOLOv4-Tiny |
| 6. RUNTIME(S) | Deepstream |
| 8. Supported Hardware | All NVIDIA GPUS INCLUDING JETSON DEVICES |
| 5. Output | TYPE: LABEL, BOUNDING BOX; LABEL CLASSES: LPD; DIMENSION: 2D; RESOLUTION: LABELS-1X1, BBOX-1X4 |
| 3. Model Architecture | CSPDarknet-Tiny |
| 7. Supported OS | LINUX, LINUX4TEGRA |
| 1. Description | Detects a license plate from a crop of a car. |
| 4. Input | TYPE: RGB IMAGE; DIMENSION: 2D; RESOLUTION: 720x1168x3 |
05/25/2022 3:39 PM UTC135.06 MBAccuracy: 98120 EpochsBatch Size: 1GPU: V100Copied!
05/25/2022 3:39 PM UTC135.06 MBAccuracy: 98120 EpochsBatch Size: 1GPU: V100
Copied!
1. MODEL OVERVIEW
| Key | Value |
|---|---|
| 2. Model Architecture | YOLOv4-Tiny |
| 6. RUNTIME(S) | Deepstream |
| 8. Supported Hardware | All NVIDIA GPUS INCLUDING JETSON DEVICES |
| 5. Output | TYPE: LABEL, BOUNDING BOX; LABEL CLASSES: LPD; DIMENSION: 2D; RESOLUTION: LABELS-1X1, BBOX-1X4 |
| 3. Model Architecture | CSPDarknet-Tiny |
| 7. Supported OS | LINUX, LINUX4TEGRA |
| 1. Description | Detects a license plate from a crop of a car. |
| 4. Input | TYPE: RGB IMAGE; DIMENSION: 2D; RESOLUTION: 720x1168x3 |
11/24/2021 5:51 AM UTC5.34 MBAccuracy: 98120 EpochsBatch Size: 1GPU: V100
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11/24/2021 5:50 AM UTC67.53 MBAccuracy: 98120 EpochsBatch Size: 1GPU: V100
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08/24/2021 3:27 PM UTC1.43 MBAccuracy: 98120 EpochsBatch Size: 1GPU: V100
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08/24/2021 3:26 PM UTC85.83 MBAccuracy: 98120 EpochsBatch Size: 1GPU: V100
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