moving utils from perception to pollen_vision

Author: apirrone

README.md

@@ -32,7 +32,7 @@
 <!-- # Pollen Vision -->
 
 <div align="center">
- 
+
 ![demo](assets/pollen_vision_intro.gif)
 
 </div>
@@ -46,7 +46,7 @@ import cv2
 
 from pollen_vision.vision_models.object_detection import OwlVitWrapper
 from pollen_vision.vision_models.object_segmentation import MobileSamWrapper
-from pollen_vision.perception.utils import Annotator, get_bboxes
+from pollen_vision.utils import Annotator, get_bboxes
 
 
 owl = OwlVitWrapper()
@@ -81,7 +81,7 @@ We continue to work on adding new models that could be useful for robotics perce
 
 We chose to focus on zero-shot models to make it easier to use and deploy. Zero-shot models can recognize objects or segment them based on text queries, without needing to be fine-tuned on annotated datasets.
 
-Right now, we support: 
+Right now, we support:
 #### Object detection
 - `Yolo-World` for zero-shot object detection and localization
 - `Owl-Vit` for zero-shot object detection and localization
@@ -93,7 +93,7 @@ Right now, we support:
 #### Monocular depth estimation
 - `Depth Anything` for (non metric) monocular depth estimation
 
-Below is an example of combining `Owl-Vit` and `Mobile-Sam` to detect and segment objects in a point cloud, all live. 
+Below is an example of combining `Owl-Vit` and `Mobile-Sam` to detect and segment objects in a point cloud, all live.
 (Note: in this example, there is no temporal or spatial filtering of any kind, we display the raw outputs of the models computed independently on each frame)
 
 https://github.com/pollen-robotics/pollen-vision/assets/6552564/a5285627-9cba-4af5-aafb-6af3d1e6d40c
@@ -185,7 +185,7 @@ python pollen-vision/gradio/app.py
 <details>
 
 <summary>Examples</summary>
-    
+
 # Examples
 
 ## Vision models wrappers
@@ -199,5 +199,3 @@ Check our [example scripts](examples/camera_wrappers_examples/)!
 
 [![Twitter URL](https://img.shields.io/twitter/url?url=https%3A%2F%2Ftwitter.com%2Fpollenrobotics)](https://twitter.com/pollenrobotics)
 [![Linkedin URL](https://img.shields.io/badge/LinkedIn-0077B5?style=for-the-badge&logo=linkedin&logoColor=white)](https://www.linkedin.com/company/pollen-robotics/mycompany/)
-
-

examples/camera_wrappers_examples/live_pcl.py

@@ -7,7 +7,7 @@
     get_config_file_path,
     get_config_files_names,
 )
-from pollen_vision.perception.utils.pcl_visualizer import PCLVisualizer
+from pollen_vision.utils.pcl_visualizer import PCLVisualizer
 
 valid_configs = get_config_files_names()
 

examples/vision_models_examples/Object Detection OWL-ViT.ipynb

@@ -176,7 +176,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from pollen_vision.perception.utils import Annotator"
+    "from pollen_vision.utils import Annotator"
    ]
   },
   {

examples/vision_models_examples/Object Segmentation - Mobile SAM.ipynb

@@ -194,7 +194,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from pollen_vision.perception.utils import get_bboxes\n",
+    "from pollen_vision.utils import get_bboxes\n",
     "\n",
     "bboxes = get_bboxes(predictions)"
    ]
@@ -218,7 +218,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from pollen_vision.perception.utils import Annotator"
+    "from pollen_vision.utils import Annotator"
    ]
   },
   {

gradio/app.py

@@ -10,7 +10,7 @@
 import numpy as np
 import numpy.typing as npt
 from datasets import load_dataset
-from pollen_vision.perception.utils import Annotator, get_bboxes
+from pollen_vision.utils import Annotator, get_bboxes
 from pollen_vision.vision_models.object_detection import OwlVitWrapper
 from pollen_vision.vision_models.object_segmentation import MobileSamWrapper
 

pollen_vision/pollen_vision/perception/perception.py

@@ -6,7 +6,7 @@
 import numpy as np
 import numpy.typing as npt
 from pollen_vision.camera_wrappers import CameraWrapper
-from pollen_vision.perception.utils import (
+from pollen_vision.utils import (
     Annotator,
     ObjectsFilter,
     get_bboxes,