migrated to poetry, dataclasses

gui.py

@@ -1,6 +1,6 @@
 import cv2
 
-img = cv2.imread('nebula2.jpg', 0)
+img = cv2.imread('sheep.png')
 
 cv2.imshow('image', img)
 k = cv2.waitKey(0)

pyproject.toml

@@ -0,0 +1,23 @@
+[tool.poetry]
+name = "vision"
+version = "0.1.0"
+description = "Jupyter scratchpad for playing with computer vision"
+authors = ["andy <andy@sarsoo.xyz>"]
+
+[tool.poetry.dependencies]
+python = "^3.8"
+numpy = "^1.19.5"
+opencv-python = "^4.5.1"
+scikit-learn = "^0.24.1"
+scipy = "^1.6.0"
+jupyterlab = {version = "^3.0.6", optional = true}
+ipykernel = "^5.4.3"
+
+[tool.poetry.dev-dependencies]
+
+[tool.poetry.extras]
+jupyter = ["jupyterlab"]
+
+[build-system]
+requires = ["poetry-core>=1.0.0"]
+build-backend = "poetry.core.masonry.api"

requirements.txt

@@ -1,78 +0,0 @@
-anyio==2.0.2
-argon2-cffi==20.1.0
-async-generator==1.10
-attrs==20.3.0
-Babel==2.9.0
-backcall==0.2.0
-bleach==3.2.1
-certifi==2020.12.5
-cffi==1.14.4
-chardet==4.0.0
-colorama==0.4.4
-cycler==0.10.0
-decorator==4.4.2
-defusedxml==0.6.0
-entrypoints==0.3
-idna==2.10
-importlib-metadata==3.3.0
-ipykernel==5.4.2
-ipython==7.19.0
-ipython-genutils==0.2.0
-jedi==0.18.0
-Jinja2==2.11.2
-joblib==1.0.0
-json5==0.9.5
-jsonschema==3.2.0
-jupyter-client==6.1.7
-jupyter-core==4.7.0
-jupyter-server==1.1.3
-jupyterlab==3.0.0
-jupyterlab-pygments==0.1.2
-jupyterlab-server==2.0.0
-kiwisolver==1.3.1
-MarkupSafe==1.1.1
-matplotlib==3.3.3
-mistune==0.8.4
-more-itertools==8.6.0
-nbclassic==0.2.5
-nbclient==0.5.1
-nbconvert==6.0.7
-nbformat==5.0.8
-nest-asyncio==1.4.3
-notebook==6.1.6
-numpy==1.19.4
-opencv-python==4.4.0.46
-packaging==20.8
-pandas==1.2.0
-pandocfilters==1.4.3
-parso==0.8.1
-pexpect==4.8.0
-pickleshare==0.7.5
-Pillow==8.0.1
-prometheus-client==0.9.0
-prompt-toolkit==3.0.8
-ptyprocess==0.7.0
-pycparser==2.20
-Pygments==2.7.3
-pyparsing==2.4.7
-pyrsistent==0.17.3
-python-dateutil==2.8.1
-pytz==2020.5
-pywin32==300
-pywinpty==0.5.7
-pyzmq==20.0.0
-requests==2.25.1
-scikit-learn==0.24.0
-scipy==1.6.0
-Send2Trash==1.5.0
-six==1.15.0
-sniffio==1.2.0
-terminado==0.9.1
-testpath==0.4.4
-threadpoolctl==2.1.0
-tornado==6.1
-traitlets==5.0.5
-urllib3==1.26.2
-wcwidth==0.2.5
-webencodings==0.5.1
-zipp==3.4.0

vision/maths/precision_recall.py

@@ -1,12 +1,13 @@
+from dataclasses import dataclass
 from typing import List
 from vision.model import Image
 
 
+@dataclass
 class PrecisionRecall:
-    def __init__(self, precision, recall, ap):
-        self.precision = precision
-        self.recall = recall
-        self.ap = ap
+    precision: float
+    recall: float
+    ap: float
 
 
 def get_precision(images: List[Image], test):

vision/util/edge.py

@@ -1,3 +1,4 @@
+from dataclasses import dataclass
 from vision.model import Image
 from typing import List
 import numpy as np
@@ -6,10 +7,10 @@ import math as m
 import cv2
 
 
+@dataclass
 class Edge:
-    def __init__(self, magnitude: np.array, angle: np.array):
-        self.magnitude = magnitude
-        self.angle = angle
+    magnitude: np.array
+    angle: np.array
 
 
 def get_edge_angle_hist(edge: Edge, bins: int, threshold: float):

vision/visualsearch/__init__.py

@@ -1,3 +1,4 @@
+from dataclasses import dataclass
 from typing import List
 import random
 import numpy as np
@@ -8,14 +9,11 @@ import logging
 logger = logging.getLogger(__name__)
 
 
+@dataclass
 class QueryResult:
-    def __init__(self,
-                 sorted_images: List[Image],
-                 query_image: Image,
-                 precision_recall: pr.PrecisionRecall):
-        self.sorted_images = sorted_images
-        self.query_image = query_image
-        self.precision_recall = precision_recall
+    sorted_images: List[Image]
+    query_image: Image
+    precision_recall: pr.PrecisionRecall
 
 
 def run_query(images: List[Image], distance_measure=None, query_index=None):