fix info new release

Author: Koldim2001

README.md

@@ -115,7 +115,7 @@ Class implementing cropping and passing crops through a neural network for detec
 | model                 | ultralytics model      | None         | Pre-initialized model object. If provided, the model will be used directly instead of loading from model_path. |
 | imgsz                 | int                    | 640          | Size of the input image for inference YOLO.                                                                    |
 | conf                  | float                  | 0.25          | Confidence threshold for detections YOLO.                                                                      |
-| iou                   | float                  | 0.7          | IoU threshold for non-maximum suppression YOLOv8 of single  crop.                                              |
+| iou                   | float                  | 0.7          | IoU threshold for non-maximum suppression YOLO of single  crop.                                              |
 | classes_list          | List[int] or None      | None         | List of classes to filter detections. If None, all classes are considered.                                     |
 | segment               | bool                   | False        | Whether to perform segmentation (if the model supports it).                                                    |
 | shape_x               | int                    | 700          | Size of the crop in the x-coordinate.                                                                          |

patched_yolo_infer/README.md

@@ -27,7 +27,7 @@ __Check this Colab examples:__
 
 Patch-Based-Inference Example - [**Open in Colab**](https://colab.research.google.com/drive/1XCpIYLMFEmGSO0XCOkSD7CcD9SFHSJPA?usp=sharing)
 
-Example of using various functions for visualizing basic YOLOv8/v9 inference results - [**Open in Colab**](https://colab.research.google.com/drive/1eM4o1e0AUQrS1mLDpcgK9HKInWEvnaMn?usp=sharing)
+Example of using various functions for visualizing basic YOLO inference results - [**Open in Colab**](https://colab.research.google.com/drive/1eM4o1e0AUQrS1mLDpcgK9HKInWEvnaMn?usp=sharing)
 
 
 ## Usage
@@ -89,9 +89,9 @@ Class implementing cropping and passing crops through a neural network for detec
 - **model** (*ultralytics model*) Pre-initialized model object. If provided, the model will be used directly instead of loading from model_path.
 - **imgsz** (*int*): Size of the input image for inference YOLO.
 - **conf** (*float*): Confidence threshold for detections YOLO.
-- **iou** (*float*): IoU threshold for non-maximum suppression YOLOv8 of single crop.
+- **iou** (*float*): IoU threshold for non-maximum suppression YOLO of single crop.
 - **classes_list** (*List[int] or None*): List of classes to filter detections. If None, all classes are considered. Defaults to None.
-- **segment** (*bool*): Whether to perform segmentation (YOLOv8-seg).
+- **segment** (*bool*): Whether to perform segmentation (YOLO-seg).
 - **shape_x** (*int*): Size of the crop in the x-coordinate.
 - **shape_y** (*int*): Size of the crop in the y-coordinate.
 - **overlap_x** (*float*): Percentage of overlap along the x-axis.

setup.py

@@ -8,7 +8,7 @@
     long_description = "\n" + fh.read()
 
 
-VERSION = '1.3.4'
+VERSION = '1.3.5'
 DESCRIPTION = '''Patch-Based-Inference for detection/segmentation of small objects in images.'''
 
 setup(
@@ -30,25 +30,30 @@
     ],
     keywords=[
         "python",
-        "yolov8",
-        "yolov9",
-        "yolov10",
-        "yolo11",
+        "YOLOv8",
+        "YOLOv9",
+        "YOLOv10",
+        "YOLO11",
+        "YOLO-seg",
+        "YOLO-pose",
         "rtdetr",
         "fastsam",
         "sahi",
         "object detection",
         "instance segmentation",
         "patch-based inference",
+        "patch-based",
         "small object detection",
-        "yolov8-seg",
         "image patching",
-        "yolo visualization",
+        "YOLO visualization",
+        "YOLO-seg visualization",
+        "YOLO-pose visualization",
         "slice-based inference",
         "slicing inference",
         "inference visualization",
         "patchify",
         "ultralytics",
+        "computer-vision"
     ],
     classifiers=[
         "Development Status :: 5 - Production/Stable",