Upload Sensitive Detector v1.1.0

README.md

@@ -10,12 +10,15 @@ tags:
 - pyronear
 ---
 
-# pyronear/yolo11s_sensitive-detector_v1.0.0
+# pyronear/yolo11s_sensitive-detector
 
 Pyronear YOLO model for early wildfire smoke detection.
 
 **Release name:** Sensitive Detector
-**Version:** v1.0.0
+**Latest version:** v1.1.0
+
+Each release is a git tag on this repo (e.g. `v1.1.0`). Pin a version with
+`revision="v1.1.0"` in `hf_hub_download` / `snapshot_download`.
 
 ## Model details
 
@@ -25,8 +28,8 @@ Pyronear YOLO model for early wildfire smoke detection.
 | Image size | 1024 |
 | Epochs | 50 |
 | Optimizer | AdamW |
-| Weights SHA-256 | `f6f7868833804965...` |
-| Training data MD5 | `fcd56c8728d160e9...` |
+| Weights SHA-256 | `a9bfa11c559e4b22...` |
+| Training data MD5 | `409302377938ce2a...` |
 
 ## Files
 
@@ -58,7 +61,7 @@ import onnxruntime as ort
 import numpy as np
 from PIL import Image
 
-path = hf_hub_download(repo_id="pyronear/yolo11s_sensitive-detector_v1.0.0", filename="onnx_cpu.tar.gz")
+path = hf_hub_download(repo_id="pyronear/yolo11s_sensitive-detector", filename="onnx_cpu.tar.gz")
 session = ort.InferenceSession(path, providers=["CPUExecutionProvider"])
 
 img = Image.open("image.jpg").resize((1024, 1024))
@@ -78,7 +81,8 @@ tar -xzf ncnn_cpu.tar.gz
 ```python
 from huggingface_hub import snapshot_download
 
-local_dir = snapshot_download(repo_id="pyronear/yolo11s_sensitive-detector_v1.0.0")
+local_dir = snapshot_download(repo_id="pyronear/yolo11s_sensitive-detector")  # latest
+local_dir = snapshot_download(repo_id="pyronear/yolo11s_sensitive-detector", revision="v1.1.0")  # pinned
 ```
 
 ### Pyronear engine (sequential smoke detection)

best.pt

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:f6f78688338049652a00f3804bd171ed04a4f3284f4c5877a4b21aaf92fde039
+oid sha256:a9bfa11c559e4b221c43bb24a0ec0857bc75ec653283ba6146aef44c088da51a
 size 19225626

manifest.yaml

@@ -1,22 +1,22 @@
 model:
   weights:
     filepath: data/02_models/yolo/best/weights/best.pt
-    sha256: f6f78688338049652a00f3804bd171ed04a4f3284f4c5877a4b21aaf92fde039
+    sha256: a9bfa11c559e4b221c43bb24a0ec0857bc75ec653283ba6146aef44c088da51a
   model_type: yolo11s.pt
   dvc:
     path: ./data/02_models/yolo/best
     hash: md5
-    md5: ef33a081ba731d593ab9a0fe4800dce6.dir
-    size: 44144497
+    md5: 52216f9194f58306d24d4802af43394a.dir
+    size: 44857368
     nfiles: 24
 data:
   data_yaml: data/01_model_input/yolo_train_val_small/datasets/data.yaml
   dvc:
     path: ./data/01_model_input/yolo_train_val
     hash: md5
-    md5: fcd56c8728d160e957bf0acd8049368d.dir
-    size: 1780235401
-    nfiles: 30387
+    md5: 409302377938ce2a82f5338f3145cbbc.dir
+    size: 1914167911
+    nfiles: 32201
 train_run_args:
   task: detect
   mode: train
@@ -180,20 +180,20 @@ dvc_lock:
       cmd:
         - uv run python ./scripts/data/model_input/build.py --input-dir ./data/01_model_input/yolo_train_val
           --output-dir ./data/01_model_input/yolo_train_val_small --sampling-ratio
-          1 --random-seed 0 --remove-background --loglevel info
+          1 --random-seed 0 --exclude-background --loglevel info
         - uv run python ./scripts/model/yolo/train.py --data ./data/01_model_input/yolo_train_val_small/datasets/data.yaml
           --config ./scripts/model/yolo/configs/best.yaml --output-dir ./data/02_models/yolo/
           --experiment-name best --loglevel info
       deps:
         - path: ./data/01_model_input/yolo_train_val
           hash: md5
-          md5: fcd56c8728d160e957bf0acd8049368d.dir
-          size: 1780235401
-          nfiles: 30387
+          md5: 409302377938ce2a82f5338f3145cbbc.dir
+          size: 1914167911
+          nfiles: 32201
         - path: ./scripts/data/model_input/build.py
           hash: md5
-          md5: 90d0643f57bff22e2005b43e33eca658
-          size: 7200
+          md5: f745456171e8a8b24faca0e5f2bc0a22
+          size: 7800
         - path: ./scripts/model/yolo/configs/best.yaml
           hash: md5
           md5: 82ab9c26b11cfc5f72e1398bfceeb838
@@ -205,8 +205,8 @@ dvc_lock:
       outs:
         - path: ./data/02_models/yolo/best
           hash: md5
-          md5: ef33a081ba731d593ab9a0fe4800dce6.dir
-          size: 44144497
+          md5: 52216f9194f58306d24d4802af43394a.dir
+          size: 44857368
           nfiles: 24
     build_manifest_yolo_best:
       cmd:
@@ -215,8 +215,8 @@ dvc_lock:
       deps:
         - path: ./data/02_models/yolo/best/
           hash: md5
-          md5: be5d61086d3a2b2e68e8a5dd61b14901.dir
-          size: 44003643
+          md5: 0e3617cd00b6a1985129110757bca1a0.dir
+          size: 44813862
           nfiles: 24
         - path: ./scripts/model/yolo/build_manifest.py
           hash: md5
@@ -225,8 +225,8 @@ dvc_lock:
       outs:
         - path: ./data/03_reporting/yolo/best/
           hash: md5
-          md5: d16e4d5660095fd5a38280ebea098ddc.dir
-          size: 13490
+          md5: c01eb3ce79f23e0999d3220813c01881.dir
+          size: 13529
           nfiles: 1
     export_yolo_best@onnx-cpu:
       cmd:
@@ -236,8 +236,8 @@ dvc_lock:
       deps:
         - path: ./data/02_models/yolo/best/
           hash: md5
-          md5: be5d61086d3a2b2e68e8a5dd61b14901.dir
-          size: 44003643
+          md5: 0e3617cd00b6a1985129110757bca1a0.dir
+          size: 44813862
           nfiles: 24
         - path: ./scripts/model/yolo/export.py
           hash: md5
@@ -246,8 +246,8 @@ dvc_lock:
       outs:
         - path: ./data/02_models/yolo-export/best/onnx/cpu
           hash: md5
-          md5: 0b4f67d18810a40cb4d783312a4bdca8.dir
-          size: 38512704
+          md5: 3e101e69ac72dc3109be7afd2b61aa4a.dir
+          size: 38532985
           nfiles: 1
     export_yolo_best@onnx-mps:
       cmd:
@@ -278,8 +278,8 @@ dvc_lock:
       deps:
         - path: ./data/02_models/yolo/best/
           hash: md5
-          md5: be5d61086d3a2b2e68e8a5dd61b14901.dir
-          size: 44003643
+          md5: 0e3617cd00b6a1985129110757bca1a0.dir
+          size: 44813862
           nfiles: 24
         - path: ./scripts/model/yolo/export.py
           hash: md5
@@ -288,8 +288,8 @@ dvc_lock:
       outs:
         - path: ./data/02_models/yolo-export/best/ncnn/cpu
           hash: md5
-          md5: e1493ed19c061ad3ec6b00caead444bd.dir
-          size: 38001888
+          md5: f6f1f2b316198f427a51b3b8335e7b7c.dir
+          size: 38001906
           nfiles: 5
     export_yolo_best@ncnn-mps:
       cmd:
@@ -314,28 +314,28 @@ dvc_lock:
           nfiles: 5
     fetch_model_input:
       cmd:
-        - uv run dvc get https://github.com/pyronear/pyro-dataset data/processed/yolo_train_val
-          --rev v2.1.0 --out ./data/01_model_input/yolo_train_val || uv run dvc get
-          git@github.com:pyronear/pyro-dataset.git data/processed/yolo_train_val --rev
-          v2.1.0 --out ./data/01_model_input/yolo_train_val
+        - uv run dvc get https://github.com/pyronear/pyro-dataset data/processed/yolo_train_val_corrected
+          --rev v4.0.0-corrected --out ./data/01_model_input/yolo_train_val || uv
+          run dvc get git@github.com:pyronear/pyro-dataset.git data/processed/yolo_train_val_corrected
+          --rev v4.0.0-corrected --out ./data/01_model_input/yolo_train_val
       outs:
         - path: ./data/01_model_input/yolo_train_val
           hash: md5
-          md5: fcd56c8728d160e957bf0acd8049368d.dir
-          size: 1780235401
-          nfiles: 30387
+          md5: 409302377938ce2a82f5338f3145cbbc.dir
+          size: 1914167911
+          nfiles: 32201
     fetch_sequential_val:
       cmd:
         - uv run dvc get https://github.com/pyronear/pyro-dataset data/processed/sequential_train_val/val
-          --rev v2.1.0 --out ./data/01_model_input/sequential_train_val/val || uv
-          run dvc get git@github.com:pyronear/pyro-dataset.git data/processed/sequential_train_val/val
-          --rev v2.1.0 --out ./data/01_model_input/sequential_train_val/val
+          --rev v4.0.0-corrected --out ./data/01_model_input/sequential_train_val/val
+          || uv run dvc get git@github.com:pyronear/pyro-dataset.git data/processed/sequential_train_val/val
+          --rev v4.0.0-corrected --out ./data/01_model_input/sequential_train_val/val
       outs:
         - path: ./data/01_model_input/sequential_train_val/val
           hash: md5
-          md5: 2ca47638a4b0cc9ca7d4011376c54e45.dir
-          size: 631259421
-          nfiles: 12448
+          md5: 652f9f7e73f297b782ed68e1b4844cce.dir
+          size: 671953151
+          nfiles: 11478
     evaluate_sequential_yolo_best:
       cmd:
         - uv run python ./scripts/model/yolo/evaluate_sequential.py --model-path ./data/02_models/yolo-export/best/onnx/cpu/best.onnx
@@ -369,12 +369,12 @@ dvc_lock:
       deps:
         - path: ./data/01_model_input/sequential_train_val/val
           hash: md5
-          md5: 2ca47638a4b0cc9ca7d4011376c54e45.dir
-          size: 631259421
-          nfiles: 12448
+          md5: 652f9f7e73f297b782ed68e1b4844cce.dir
+          size: 671953151
+          nfiles: 11478
         - path: ./data/02_models/yolo/best/weights/best.pt
           hash: md5
-          md5: fea4ddc8d904fcc5ff11ad900e040837
+          md5: 550d1b91fb93e52cf233166b03405a10
           size: 19225626
         - path: predict_sequential.py
           hash: md5
@@ -383,9 +383,9 @@ dvc_lock:
       outs:
         - path: ./data/03_reporting/sequential/predictions_labels_val
           hash: md5
-          md5: cbe0e8e4d58627ca6856371246d400c2.dir
-          size: 104904
-          nfiles: 3438
+          md5: 796a49a2802fa773158ca168a680f12c.dir
+          size: 109228
+          nfiles: 3340
     optimize_sequential_val:
       cmd:
         - uv run python optimize_sequential.py --labels-dir ./data/03_reporting/sequential/predictions_labels_val
@@ -395,9 +395,9 @@ dvc_lock:
       deps:
         - path: ./data/03_reporting/sequential/predictions_labels_val
           hash: md5
-          md5: cbe0e8e4d58627ca6856371246d400c2.dir
-          size: 104904
-          nfiles: 3438
+          md5: 796a49a2802fa773158ca168a680f12c.dir
+          size: 109228
+          nfiles: 3340
         - path: optimize_sequential.py
           hash: md5
           md5: 115eb45048da93018f7ea86b5f954270
@@ -405,9 +405,9 @@ dvc_lock:
       outs:
         - path: ./data/03_reporting/sequential/grid_search_val.tsv
           hash: md5
-          md5: 8bae210202dc4210162712779346d572
-          size: 1896
+          md5: aa6f9da227c79d6ffa2903e7b9a3d18b
+          size: 1873
         - path: ./data/03_reporting/sequential/grid_search_val_top20.tsv
           hash: md5
-          md5: 42f461234b5a48ca27bb28a46afb2cd0
-          size: 975
+          md5: dd8e0aa4c8bc678deb27acbdd911c065
+          size: 973

ncnn_cpu.tar.gz

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:c44d4f6770e6eb1c281ca30207c11121ee4bbff8c58c96dc6e658f7b932ac8ce
-size 32591612
+oid sha256:db13af06fa87c896e4f298d60abf514308b6cdaeb148a15e841a85ca07e9b857
+size 32590473

onnx_cpu.tar.gz

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:e694608550f04c9367484d792921fff822715e27d6a9cba672afef88008b2d4c
-size 32603016
+oid sha256:4c9f243705a301abf76ef62803e158c8c47bf932f0c7f942816bef72660a6b40
+size 32605576