Yolo26

apps/ml-yolo/Dockerfile

@@ -51,7 +51,8 @@ RUN python3 -m venv /opt/tools-venv && \
     /opt/tools-venv/bin/pip install --no-cache-dir --upgrade pip && \
     /opt/tools-venv/bin/pip install --no-cache-dir --timeout=120 --retries=5 \
         --index-url https://download.pytorch.org/whl/cpu \
-        torch==2.8.0+cpu torchvision==0.23.0+cpu && \
+        --extra-index-url https://pypi.org/simple \
+        torch==2.8.0+cpu torchvision==0.23.0 && \
     git clone https://github.com/luxonis/tools.git /tmp/luxonis-tools && \
     cd /tmp/luxonis-tools && \
     git checkout edbe7da1a7f75833a71d65caf1028036faa81061 && \
@@ -130,21 +131,29 @@ ENV IN_DOCKER=1
 ENV ROBOPIPE_MODELCONVERTER_BIN=/opt/modelconverter-venv/bin/modelconverter
 ENV ROBOPIPE_SNPE_ROOT=/opt/snpe
 
-# Pre-download all yolo11 detection + segmentation pretrained weights into the
-# image. Ultralytics' YOLO(name) constructor calls safe_download() which has a
-# known silent-failure path: if a retry deletes a partial file and the loop
-# exits without raising, attempt_download_asset() returns a Path to a
-# non-existent file and the next torch.load() raises FileNotFoundError. By
-# baking the weights at /app (the WORKDIR), YOLO()'s first existence check
-# (`Path(file).exists()` against cwd) hits and skips the download entirely.
-# Pin to v8.3.0 — the release tag that hosts the yolo11 family weights.
+# Pre-download pretrained weights into the image. Ultralytics' YOLO(name)
+# constructor calls safe_download() which has a known silent-failure path: if
+# a retry deletes a partial file and the loop exits without raising,
+# attempt_download_asset() returns a Path to a non-existent file and the next
+# torch.load() raises FileNotFoundError. By baking the weights at /app (the
+# WORKDIR), YOLO()'s first existence check (`Path(file).exists()` against cwd)
+# hits and skips the download entirely.
+# YOLO11 weights at v8.3.0; YOLO26 weights at v8.4.0 (first release that
+# ships the yolo26 family).
 RUN cd /app && for v in \
     yolo11n yolo11s yolo11m yolo11l yolo11x \
     yolo11n-seg yolo11s-seg yolo11m-seg yolo11l-seg yolo11x-seg \
     ; do \
     curl -fL --retry 3 -o ${v}.pt \
         https://github.com/ultralytics/assets/releases/download/v8.3.0/${v}.pt; \
     done
+RUN cd /app && for v in \
+    yolo26n yolo26s yolo26m yolo26l yolo26x \
+    yolo26n-seg yolo26s-seg yolo26m-seg yolo26l-seg yolo26x-seg \
+    ; do \
+    curl -fL --retry 3 -o ${v}.pt \
+        https://github.com/ultralytics/assets/releases/download/v8.4.0/${v}.pt; \
+    done
 
 COPY app/ ./app/
 

apps/ml-yolo/app/ml/archive_patch.py

@@ -24,6 +24,13 @@
 from ..models.model_type import ModelType
 
 
+def _yolo_subtype(model_variant: str) -> str:
+    stem = Path(model_variant).stem.lower()
+    if stem.startswith("yolo26"):
+        return "yolo26"
+    return "yolov8"
+
+
 # Pre-NMS thresholds the on-device DetectionParser uses. The dashboard
 # does its own confidence filtering on top
 # (sensor.dashboard_config.confidenceThreshold), so this is a coarse
@@ -43,6 +50,7 @@ def patch_nn_archive_heads(
     archive_path: str | Path,
     model_type: ModelType,
     label_ids: list[int],
+    model_variant: str = "",
 ) -> None:
     """Mutate the NN archive at `archive_path` in-place to ensure it has a
     valid `heads` block. No-op when the file isn't an NN archive, when
@@ -118,7 +126,7 @@ def patch_nn_archive_heads(
                     "conf_threshold": _DEFAULT_CONF_THRESHOLD,
                     "max_det": _DEFAULT_MAX_DET,
                     "anchors": None,
-                    "subtype": "yolov8",
+                    "subtype": _yolo_subtype(model_variant),
                     "yolo_outputs": output_names,
                 },
                 "outputs": output_names,

apps/ml-yolo/app/ml/train_model.py

@@ -396,6 +396,7 @@ def upload_for(t: ModelOutputType) -> OutputUpload:
                     converted_path,
                     config.type,
                     config.training_config.dataset_config.label_ids,
+                    model_variant=get_model_variant(config),
                 )
                 conv_upload = upload_for(output_type)
                 _upload_to_signed_url(conv_upload, converted_path)

apps/ml-yolo/app/ml/ultralytics_config.py

@@ -10,6 +10,8 @@
     dfl, hsv_h, hsv_s, hsv_v, degrees, translate, scale, shear, perspective,
     flipud, fliplr, mosaic, mixup, copy_paste, optimizer, cos_lr, patience,
     imgsz, workers, device, amp
+Note: `dfl` is silently stripped for YOLO26 variants (DFL removed in YOLO26).
+YOLO26 variants: yolo26[n|s|m|l|x][.pt] and yolo26[n|s|m|l|x]-seg[.pt]
 Plus two ml-yolo-specific keys stripped before passthrough:
     backend          — consumed by the API dispatcher
     model_variant    — pretrained weights filename (e.g. yolo11m.pt)
@@ -35,6 +37,10 @@
 }
 
 
+def _is_yolo26(variant: str) -> bool:
+    return Path(variant).stem.lower().startswith("yolo26")
+
+
 def get_model_variant(config: ModelConfig) -> str:
     custom = config.training_config.custom_hyperparams or {}
     variant = custom.get("model_variant")
@@ -102,4 +108,6 @@ def build_train_kwargs(
     # custom_hyperparams wins over defaults but not over the dispatch kwargs above.
     for key, value in custom.items():
         kwargs[key] = value
+    if _is_yolo26(get_model_variant(config)):
+        kwargs.pop("dfl", None)
     return kwargs

apps/ml-yolo/requirements.txt

@@ -11,9 +11,8 @@ pydantic-settings==2.7.1
 python-multipart==0.0.17
 
 # ML training (no luxonis-train — this is the Ultralytics-only service).
-# 8.3.160 decouples the confusion matrix update from args.plots (so the CM
-# is populated even without plot files) and fixes the epoch-47 validation
-# plot broadcast crash. Still numpy-1.x compatible.
+# 8.4.44: first release series shipping yolo26*.pt weights (YOLO26 support).
+# YOLO11 trains identically on 8.4.x — the 8.3→8.4 bump is additive only.
 #
 # torch is PINNED to 2.8.0 (not 2.9). In torch 2.9, `torch.onnx.export`
 # hard-imports `onnxscript` even on the legacy `dynamo=False` path, and
@@ -23,7 +22,7 @@ python-multipart==0.0.17
 # it triggers the crash. torch 2.8's legacy exporter is pure TorchScript
 # with zero onnxscript involvement, sidestepping the trap entirely. Bump
 # only when ultralytics or torch fix the upstream interaction.
-ultralytics==8.3.160
+ultralytics==8.4.44
 torch==2.8.0
 torchvision==0.23.0
 

apps/web/src/modules/model/components/AdvancedSettings/presets.ts

@@ -110,6 +110,59 @@ const ULTRALYTICS_PRESETS: HyperparamsPreset[] = [
       patience: 30,
     },
   },
+  {
+    id: "yolo26-fast",
+    name: "YOLO26 Fast",
+    description: "YOLO26 nano — NMS-free, faster CPU inference, quick iteration",
+    config: {
+      model_variant: "yolo26n",
+      imgsz: 640,
+      optimizer: "AdamW",
+      lr0: 0.001,
+      cos_lr: true,
+      patience: 20,
+      hsv_s: 0.15,
+      hsv_v: 0.2,
+      degrees: 15.0,
+      cls: 0.8,
+    },
+  },
+  {
+    id: "yolo26-accuracy",
+    name: "YOLO26 High Accuracy",
+    description:
+      "YOLO26 large at 1280px — NMS-free, edge-optimised, tuned for fine-grained classification",
+    config: {
+      model_variant: "yolo26l",
+      imgsz: 1280,
+      optimizer: "AdamW",
+      lr0: 0.001,
+      lrf: 0.01,
+      momentum: 0.937,
+      weight_decay: 0.0005,
+      cos_lr: true,
+      warmup_epochs: 5,
+      warmup_momentum: 0.8,
+      warmup_bias_lr: 0.1,
+      patience: 50,
+      box: 9.0,
+      cls: 0.8,
+      mosaic: 1.0,
+      close_mosaic: 25,
+      copy_paste: 0.2,
+      erasing: 0.4,
+      hsv_h: 0.01,
+      hsv_s: 0.15,
+      hsv_v: 0.2,
+      degrees: 15.0,
+      translate: 0.1,
+      scale: 0.5,
+      shear: 2.0,
+      perspective: 0.0005,
+      fliplr: 0.5,
+      amp: true,
+    },
+  },
 ];
 
 export const getHyperparamsPresets = (