Update dependency versions, add TensorRT execution provider (#15)

* Update dependency versions, add TensorRT execution provider

* Drop python3.8 support

* Update LICENSE

.github/workflows/python-package.yml

@@ -16,7 +16,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.8", "3.9", "3.10"]
+        python-version: ["3.9", "3.10"]
 
     steps:
     - uses: actions/checkout@v3

fast_track/object_detection/object_detector_onnx.py

@@ -30,8 +30,11 @@ def __init__(self, weights_path: str, names: List[str], image_shape: Tuple[int,
             visualize: boolean value to visualize outputs.
         """
         super().__init__(weights_path, names, image_shape, visualize)
-
-        self.providers = ['CUDAExecutionProvider', 'CPUExecutionProvider']
+        self.providers = [
+            'TensorrtExecutionProvider',
+            'CUDAExecutionProvider',
+            'CPUExecutionProvider'
+        ]
         self.session = None
         self.input_shape = None
         self.input_names = None

fast_track/object_detection/third_party/yolo_nas/yolo_nas.py

@@ -7,7 +7,6 @@
 
 from typing import List, Optional, Tuple
 
-import super_gradients
 import numpy as np
 import torch
 
@@ -35,6 +34,7 @@ def __init__(self, weights_path: str,
             visualize: boolean value to visualize outputs.
         """
         super().__init__(weights_path=weights_path, names=names, image_shape=image_shape, visualize=visualize)
+        import super_gradients
         self.model = super_gradients.training.models.get(self.weights_path, pretrained_weights=pretrained)
         if torch.cuda.is_available():
             self.model = self.model.cuda()
@@ -49,7 +49,7 @@ def detect(self,
         Returns:
             Tuple[List[int], List[float], List[np.ndarray]]: Postprocessed output (class_ids, scores, boxes).
         """
-        detections = next(iter(self.model.predict(image)))
+        detections = self.model.predict(image)
         boxes = detections.prediction.bboxes_xyxy.tolist()
         class_ids = detections.prediction.labels.astype(int).tolist()
         scores = detections.prediction.confidence.tolist()

fast_track/object_detection/third_party/yolov8/yolov8.py

@@ -8,7 +8,7 @@
 import numpy as np
 import torch
 from ultralytics import YOLO
-from ultralytics.yolo.utils import ops
+from ultralytics.utils import ops
 
 from ...object_detector import ObjectDetector
 from ...object_detector_onnx import ObjectDetectorONNX

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "fast_track"
-version = "0.6.1"
+version = "0.6.2"
 description = "Object detection and tracking pipeline"
 readme = "README.md"
 keywords = [
@@ -13,35 +13,33 @@ keywords = [
     "object-detection",
     "ai",
 ]
-license = { text = "MIT LICENE" }
+license = { file = "LICENSE.txt" }
 authors = [{ name = "Nate Haddad", email = "nhaddad2112@gmail.com" }]
 maintainers = [{ name = "Nate Haddad", email = "nhaddad2112@gmail.com" }]
 requires-python = ">=3.8, <3.11"
 dependencies = [
-    "numpy < 1.24.0", 
-    "pyyaml >= 6.0",
-    "opencv-python >= 4.6.0.66",
-    "onnxruntime >= 1.13.1",
-    "torch >= 1.13.1",
-    "scipy >= 1.9.3",
-    "ultralytics >= 8.0.92",
-    "super-gradients >= 3.1.1",
-    "pylint >= 2.17.4",
+    "numpy==1.23.0", 
+    "pyyaml == 6.0.1",
+    "opencv-python == 4.9.0.80",
+    "onnxruntime == 1.13.1",
+    "torch == 2.2.0",
+    "scipy == 1.12.0",
+    "ultralytics == 8.1.9",
+    "super-gradients == 3.6.0",
+    "pylint == 3.0.3",
 ]
 classifiers = [
-    "Programming Language :: Python :: 3.8",
     "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
-
 ]
 
 [project.optional-dependencies]
 gpu = [
-    "onnxruntime-gpu",
+    "onnxruntime-gpu==1.17.0",
 ]
 bytetrack = [
-    "lap >= 0.4.0",
-    "Cython >= 0.29.32",
+    "lap == 0.4.0",
+    "Cython == 3.0.8",
     "cython-bbox @ git+https://github.com/samson-wang/cython_bbox.git#egg=cython-bbox",
 ]
 gradio = [

run.py

@@ -1,4 +1,4 @@
-""" Run file for camera_perception """
+""" Run file for fast_track """
 
 import cv2
 import yaml