Add large rfdetr sizes and seg models upload (#434)

* new models

* fix test?

* pi_heif python 3.9 fix

* pi_heif python 3.9 fix

* version bump

Author: Matvezy

requirements.txt

@@ -7,7 +7,8 @@ numpy>=1.18.5
 opencv-python-headless==4.10.0.84
 Pillow>=7.1.2
 # https://github.com/roboflow/roboflow-python/issues/390
-pi-heif<2
+# pi-heif 1.x requires Python 3.10+
+pi-heif<2; python_version >= "3.10"
 pillow-avif-plugin<2
 python-dateutil
 python-dotenv

roboflow/__init__.py

@@ -15,7 +15,7 @@
 from roboflow.models import CLIPModel, GazeModel  # noqa: F401
 from roboflow.util.general import write_line
 
-__version__ = "1.2.12"
+__version__ = "1.2.13"
 
 
 def check_key(api_key, model, notebook, num_retries=0):

roboflow/util/image_utils.py

@@ -5,13 +5,18 @@
 import urllib
 
 # Third-party imports
-import pi_heif  # type: ignore[import-untyped]
 import pillow_avif  # type: ignore[import-untyped]
 import requests
 import yaml
 from PIL import Image
 
-pi_heif.register_heif_opener(thumbnails=False)  # Register for HEIF/HEIC
+# pi-heif requires Python 3.10+
+try:
+    import pi_heif  # type: ignore[import-untyped,import-not-found]
+
+    pi_heif.register_heif_opener(thumbnails=False)  # Register for HEIF/HEIC
+except ImportError:
+    pass
 pillow_avif = pillow_avif  # Reference pillow_avif to not remove import by accident
 
 

roboflow/util/model_processor.py

@@ -246,12 +246,21 @@ def _process_yolo(model_type: str, model_path: str, filename: str) -> str:
 
 def _process_rfdetr(model_type: str, model_path: str, filename: str) -> str:
     _supported_types = [
+        # Detection models
         "rfdetr-base",
-        "rfdetr-large",
         "rfdetr-nano",
         "rfdetr-small",
         "rfdetr-medium",
-        "rfdetr-seg-preview",
+        "rfdetr-large",
+        "rfdetr-xlarge",
+        "rfdetr-2xlarge",
+        # Segmentation models
+        "rfdetr-seg-nano",
+        "rfdetr-seg-small",
+        "rfdetr-seg-medium",
+        "rfdetr-seg-large",
+        "rfdetr-seg-xlarge",
+        "rfdetr-seg-2xlarge",
     ]
     if model_type not in _supported_types:
         raise ValueError(f"Model type {model_type} not supported. Supported types are {_supported_types}")