Feature/update (#19)

* pillow update

* pre-commit hook adjusted

* README adjusted

* adjustment of pre-commit hook

* formatting

.pre-commit-config.yaml

@@ -10,7 +10,7 @@ repos:
     rev: v1.4.1
     hooks:
     - id: mypy
-      args: ["--exclude=\"((?:logs|datasets|output|frames_detected|model_weights|venv|yolov[0-9]))\"", "--ignore-missing-imports"]
+      args: ["--exclude=\"((?:logs|datasets|output|PixelFormer|frames_detected|model_weights|venv|yolov[0-9]))\"", "--ignore-missing-imports"]
 
   - repo: local
     hooks:
@@ -29,4 +29,5 @@ repos:
   - repo: https://github.com/PyCQA/pydocstyle
     rev: 6.3.0
     hooks:
-      - id: pydocstyle
+      - id: pydocstyle
+        args: ["--ignore-self-only-init", "--ignore=D100,D104,D213,D203,D404", "--match-dir=\"^(?:(?!logs|datasets|output|PixelFormer|frames_detected|model_weights|notebooks|venv|yolov[0-9]).)*$\""]

README.md

@@ -49,6 +49,7 @@ Running the code can be done in two ways:
 9. Download the YoloV4 weights from here: https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v3_optimal/yolov4.weights
 10. Place the weights in that folder: `speed_estimation/model_weights/`
 11. Update the paths in `speed_estimation/paths.py` (detailed information in Section Configuration).
+12. Activate the pre-commit hook: `pre-commit install` (the hook will then be installed in this directory `.git/hooks/pre-commit`)
 
 ### Docker Setup
 

environment.yml

@@ -81,7 +81,7 @@ dependencies:
       - packaging==23.0
       - pandas==1.5.2
       - pathspec==0.11.1
-      - pillow==10.0.1
+      - pillow==10.2.0
       - platformdirs==3.8.0
       - plotly==5.13.0
       - pre-commit==3.3.3

environment_mac.yml

@@ -81,7 +81,7 @@ dependencies:
       - packaging==23.0
       - pandas==1.5.2
       - pathspec==0.11.1
-      - pillow==10.0.1
+      - pillow==10.2.0
       - platformdirs==3.8.0
       - plotly==5.13.0
       - pre-commit==3.3.3

speed_estimation/get_fps.py

@@ -4,6 +4,7 @@
 should be analyzed.
 This module will only be used if the FPS are not defined in speed_estimation/config.ini
 """
+
 import time
 
 import cv2

speed_estimation/modules/depth_map/custom_pixelformer/utils.py

@@ -115,9 +115,7 @@ def __init__(self, variance_focus):
 
     def forward(self, depth_est, depth_gt, mask):
         d = torch.log(depth_est[mask]) - torch.log(depth_gt[mask])
-        return (
-            torch.sqrt((d**2).mean() - self.variance_focus * (d.mean() ** 2)) * 10.0
-        )
+        return torch.sqrt((d**2).mean() - self.variance_focus * (d.mean() ** 2)) * 10.0
 
 
 def flip_lr(image):

speed_estimation/modules/streaming/stream_video.py

@@ -7,6 +7,7 @@
 
 NOTE: This module is work in progress and not integrated into the speed estimation pipeline yet.
 """
+
 import argparse
 import math
 import subprocess as sp

speed_estimation/speed_estimation.py

@@ -21,6 +21,7 @@
 6. As soon as the calibration is done, do the speed estimation based on the scaling factor and the
 detected bounding boxes for the vehicles.
 """
+
 import argparse
 import configparser
 import json

speed_estimation/utils/speed_estimation.py

@@ -1,4 +1,5 @@
 """The utility functions and classes for the speed estimation pipeline."""
+
 from dataclasses import dataclass
 from enum import Enum
 from typing import List