Update model weights

README.md

@@ -1,12 +1,10 @@
 ---
-license: mit
 tags:
-- deepforest
+- model_hub_mixin
+- pytorch_model_hub_mixin
 ---
 
-# Bird Detection in RGB Airborne Imagery
-The model was initially described in [Ecological Applications](https://esajournals.onlinelibrary.wiley.com/doi/abs/10.1002/eap.2694). From the abstract
-
->
- Using over 250,000 annotations from 13 projects from around the world, we develop a general bird detection model that achieves over 65% recall and 50% precision on novel aerial data without any local training despite differences in species, habitat, and imaging methodology. Fine-tuning this model with only 1000 local annotations increases these values to an average of 84% recall and 69% precision by building on the general features learned from other data sources. 
- >
+This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
+- Code: [More Information Needed]
+- Paper: [More Information Needed]
+- Docs: [More Information Needed]

config.json

@@ -1,12 +1,16 @@
 {
   "config_args": null,
   "config_file": "deepforest_config.yml",
+  "detections_per_img": 300,
   "existing_train_dataloader": null,
   "existing_val_dataloader": null,
   "label_dict": {
     "Bird": 0
   },
   "model": null,
+  "nms_thresh": 0.05,
   "num_classes": 1,
+  "score_thresh": 0.25,
+  "topk_candidates": 1000,
   "transforms": null
 }

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2cff5f208261a9bb5b2dea85b9e6b15163742a64145fa9a10d273be1b4db083a
-size 129049980
+oid sha256:00efa0075cd38ddba1f4b26053394ff99961ce2e052cce2ec77633e4eb4fcf6c
+size 129048172