Instructions to use ConservationDrones/DroneMegaDetector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ConservationDrones/DroneMegaDetector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="ConservationDrones/DroneMegaDetector")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("ConservationDrones/DroneMegaDetector") model = AutoModelForObjectDetection.from_pretrained("ConservationDrones/DroneMegaDetector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload 5 files
Browse files- .gitattributes +1 -0
- config.json +119 -0
- conversion_checks.json +157 -0
- example_annotated.jpg +3 -0
- model.safetensors +3 -0
- preprocessor_config.json +25 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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example_annotated.jpg filter=lfs diff=lfs merge=lfs -text
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config.json
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{
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"activation_dropout": 0.0,
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"activation_function": "silu",
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"architectures": [
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"RfDetrForObjectDetection"
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],
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"attention_bias": true,
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"attention_dropout": 0.0,
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"auxiliary_loss": true,
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"backbone_config": {
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"dtype": "float32",
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.0,
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"hidden_size": 384,
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"layer_norm_eps": 1e-06,
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"model_type": "rf_detr_dinov2",
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"num_attention_heads": 6,
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"num_channels": 3,
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"num_hidden_layers": 12,
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"stage_names": [
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"stage3",
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"stage4",
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"stage5",
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"stage6",
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"stage7",
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"stage8",
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"stage9",
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"stage10",
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"stage11",
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"stage12"
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"bbox_cost": 5,
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"c2f_num_blocks": 3,
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"class_cost": 2,
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"class_loss_coefficient": 1,
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"d_model": 256,
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"decoder_activation_function": "relu",
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"decoder_cross_attention_heads": 16,
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"decoder_layers": 4,
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"decoder_n_points": 2,
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"decoder_self_attention_heads": 8,
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"dice_loss_coefficient": 1,
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"disable_custom_kernels": true,
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"dropout": 0.1,
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"dtype": "float32",
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"eos_coefficient": 0.1,
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"focal_alpha": 0.25,
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"giou_cost": 2,
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"group_detr": 13,
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"hidden_expansion": 0.5,
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"id2label": {
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"0": "person",
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"2": "vehicle",
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"3": "unused_legacy_slot"
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},
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"init_std": 0.02,
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"label2id": {
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},
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"layer_norm_eps": 1e-05,
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"segmentation_head_activation_function": "gelu",
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"transformers_version": "5.18.0"
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}
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conversion_checks.json
ADDED
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{
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"source": "/Users/josh/code/boem-genai/DroneMegaDetector_RFDETRMedium.pth",
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"0": "person",
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"1": "animal",
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"2": "vehicle",
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| 139 |
+
"max_absolute_error": 1.9140028244102325e-05,
|
| 140 |
+
"mean_absolute_error": 7.988022616367551e-07,
|
| 141 |
+
"atol": 0.0002,
|
| 142 |
+
"rtol": 0.0002
|
| 143 |
+
},
|
| 144 |
+
"native_boxes": {
|
| 145 |
+
"shape": [
|
| 146 |
+
1,
|
| 147 |
+
300,
|
| 148 |
+
4
|
| 149 |
+
],
|
| 150 |
+
"max_absolute_error": 2.770148079811463e-06,
|
| 151 |
+
"mean_absolute_error": 4.032394474988902e-08,
|
| 152 |
+
"atol": 0.0002,
|
| 153 |
+
"rtol": 0.0002
|
| 154 |
+
}
|
| 155 |
+
},
|
| 156 |
+
"detector_reference_precision": "float64 (reduces top-k near-tie sensitivity)"
|
| 157 |
+
}
|
example_annotated.jpg
ADDED
|
Git LFS Details
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:87cf3045c909b8eb2ce1cce39343a97806351c7eae5a6e5cb48f96fc0c20cf1b
|
| 3 |
+
size 141400024
|
preprocessor_config.json
ADDED
|
@@ -0,0 +1,25 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"do_convert_annotations": true,
|
| 3 |
+
"do_normalize": true,
|
| 4 |
+
"do_pad": true,
|
| 5 |
+
"do_rescale": true,
|
| 6 |
+
"do_resize": true,
|
| 7 |
+
"format": "coco_detection",
|
| 8 |
+
"image_mean": [
|
| 9 |
+
0.485,
|
| 10 |
+
0.456,
|
| 11 |
+
0.406
|
| 12 |
+
],
|
| 13 |
+
"image_processor_type": "RfDetrImageProcessor",
|
| 14 |
+
"image_std": [
|
| 15 |
+
0.229,
|
| 16 |
+
0.224,
|
| 17 |
+
0.225
|
| 18 |
+
],
|
| 19 |
+
"resample": 2,
|
| 20 |
+
"rescale_factor": 0.00392156862745098,
|
| 21 |
+
"size": {
|
| 22 |
+
"height": 1280,
|
| 23 |
+
"width": 1280
|
| 24 |
+
}
|
| 25 |
+
}
|