Adds support for YOLOv12 model upload

roboflow/__init__.py

@@ -15,7 +15,7 @@
 from roboflow.models import CLIPModel, GazeModel  # noqa: F401
 from roboflow.util.general import write_line
 
-__version__ = "1.1.56"
+__version__ = "1.1.57"
 
 
 def check_key(api_key, model, notebook, num_retries=0):

roboflow/core/version.py

@@ -33,7 +33,7 @@
 from roboflow.util.annotations import amend_data_yaml
 from roboflow.util.general import write_line
 from roboflow.util.model_processor import process
-from roboflow.util.versions import get_wrong_dependencies_versions
+from roboflow.util.versions import get_wrong_dependencies_versions, normalize_yolo_model_type
 
 if TYPE_CHECKING:
     import numpy as np
@@ -477,6 +477,7 @@ def deploy(self, model_type: str, model_path: str, filename: str = "weights/best
             model_path (str): File path to the model weights to be uploaded.
             filename (str, optional): The name of the weights file. Defaults to "weights/best.pt".
         """
+        model_type = normalize_yolo_model_type(model_type)
         zip_file_name = process(model_type, model_path, filename)
 
         if zip_file_name is None:

roboflow/core/workspace.py

@@ -19,6 +19,7 @@
 from roboflow.util.image_utils import load_labelmap
 from roboflow.util.model_processor import process
 from roboflow.util.two_stage_utils import ocr_infer
+from roboflow.util.versions import normalize_yolo_model_type
 
 
 class Workspace:
@@ -596,6 +597,7 @@ def deploy_model(
             if project_id not in user_projects:
                 raise ValueError(f"Project {project_id} is not accessible in this workspace")
 
+        model_type = normalize_yolo_model_type(model_type)
         zip_file_name = process(model_type, model_path, filename)
 
         if zip_file_name is None:

roboflow/roboflowpy.py

@@ -81,7 +81,8 @@ def upload_model(args):
 
     if args.version_number is not None:
         # Deploy to specific version
-        project = workspace.project(args.project)
+        project_id = args.project[0] if isinstance(args.project, list) else args.project
+        project = workspace.project(project_id)
         version = project.version(args.version_number)
         version.deploy(str(args.model_type), str(args.model_path), str(args.filename))
     else:

roboflow/util/model_processor.py

@@ -15,20 +15,18 @@ def process(model_type: str, model_path: str, filename: str) -> str:
 
 
 def _get_processor_function(model_type: str) -> Callable:
-    if model_type.startswith("yolo11"):
-        model_type = model_type.replace("yolo11", "yolov11")
-
     supported_models = [
         "yolov5",
         "yolov7-seg",
         "yolov8",
         "yolov9",
+        "yolov10",
+        "yolov11",
+        "yolov12",
         "yolonas",
         "paligemma",
         "paligemma2",
-        "yolov10",
         "florence-2",
-        "yolov11",
     ]
 
     if not any(supported_model in model_type for supported_model in supported_models):
@@ -59,6 +57,9 @@ def _get_processor_function(model_type: str) -> Callable:
     if "yolonas" in model_type:
         return _process_yolonas
 
+    if "yolov12" in model_type:
+        return _process_yolov12
+
     return _process_yolo
 
 
@@ -195,6 +196,46 @@ def _process_yolo(model_type: str, model_path: str, filename: str) -> str:
     return zip_file_name
 
 
+def _process_yolov12(model_type: str, model_path: str, filename: str) -> str:
+    # For YOLOv12, since it uses a special Ultralytics version,
+    # state dict extraction and model artifacts are handled during model conversion
+
+    print(
+        "Note: Model must be trained using ultralytics from https://github.com/sunsmarterjie/yolov12 "
+        "or through the Roboflow platform"
+    )
+
+    # Check if model_path exists
+    if not os.path.exists(model_path):
+        raise FileNotFoundError(f"Model path {model_path} does not exist.")
+
+    # Find any .pt file in model path
+    model_files = os.listdir(model_path)
+    pt_file = next((f for f in model_files if f.endswith(".pt")), None)
+
+    if pt_file is None:
+        raise RuntimeError("No .pt model file found in the provided path")
+
+    # Copy the .pt file to weights.pt if not already named weights.pt
+    if pt_file != "weights.pt":
+        shutil.copy(os.path.join(model_path, pt_file), os.path.join(model_path, "weights.pt"))
+
+    required_files = ["weights.pt"]
+
+    optional_files = ["results.csv", "results.png", "model_artifacts.json"]
+
+    zip_file_name = "roboflow_deploy.zip"
+    with zipfile.ZipFile(os.path.join(model_path, zip_file_name), "w") as zipMe:
+        for file in required_files:
+            zipMe.write(os.path.join(model_path, file), arcname=file, compress_type=zipfile.ZIP_DEFLATED)
+
+        for file in optional_files:
+            if os.path.exists(os.path.join(model_path, file)):
+                zipMe.write(os.path.join(model_path, file), arcname=file, compress_type=zipfile.ZIP_DEFLATED)
+
+    return zip_file_name
+
+
 def _process_huggingface(
     model_type: str, model_path: str, filename: str = "fine-tuned-paligemma-3b-pt-224.f16.npz"
 ) -> str:

roboflow/util/versions.py

@@ -89,3 +89,9 @@ def _wrapper(*args, **kwargs):
         return _wrapper
 
     return _inner
+
+
+def normalize_yolo_model_type(model_type: str) -> str:
+    model_type = model_type.replace("yolo11", "yolov11")
+    model_type = model_type.replace("yolo12", "yolov12")
+    return model_type