Merge branch 'main' of https://arnweb.nl/gitea/arne/EV5_Beeldherk_Bomen
This commit is contained in:
commit
158b6bf273
47
src/helpers/logger.py
Normal file
47
src/helpers/logger.py
Normal file
@ -0,0 +1,47 @@
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import pathlib
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import datetime
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now = datetime.datetime.now()
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class Logger:
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def __init__(self, path):
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self.fileName = pathlib.Path(
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path, f"result-{now.strftime('%Y-%m-%dT%H.%M.%S')}.csv"
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)
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self.file = open(self.fileName, "x")
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self.first = True
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self.index = []
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self.data = []
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def add(self, name: str, value):
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self.index.append(name)
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self.data.append(value)
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def csv(self, input):
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result = ""
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for idx, item in enumerate(input):
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result += str(item)
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if idx != (len(input) - 1):
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result += ", "
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result += "\n"
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print(result)
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return result
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def update(self):
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if self.first:
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self.first = False
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self.file.write(self.csv(self.index))
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self.file.write(self.csv(self.data))
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# Clear data
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self.index = []
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self.data = []
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def __del__(self):
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print("Log file closed!")
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self.file.close()
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220
src/suite.py
220
src/suite.py
@ -9,11 +9,13 @@ import cv2
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import time
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import matplotlib.pyplot as plt
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import json
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from helpers.statistics import imgStats
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import datetime
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import os
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import copy
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from helpers.statistics import imgStats
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from helpers.logger import Logger
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## UI config load
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PROJECT_PATH = pathlib.Path(__file__).parent
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PROJECT_UI = "./src/helpers/gui/main.ui"
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@ -23,6 +25,9 @@ CONFIG_PATH = "./src/config/config.json"
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config_file = open(CONFIG_PATH)
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config_json = json.load(config_file)
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log = Logger(config_json["out"])
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## UI class setup
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class MainApp:
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def __init__(self, master=None):
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@ -35,14 +40,14 @@ class MainApp:
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# Canvas for output images
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self.canvas = builder.get_object("output_canvas")
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self.tk_imgs = [] # Required or python will forget
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self.output = [[] for x in range(2)]
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self.tk_imgs = [] # Required or python will forget
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self.meta = builder.get_object("dataset")
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self.output = [[] for x in range(2)]
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# Keep track of images in dataset
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self.img_current = 0
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self.img_name = ""
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self.img_old = -1 ## minus 1 to enforce full update on start
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self.img_old = -1 ## minus 1 to enforce full update on start
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self.img_max = 0
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# Plots
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@ -55,12 +60,24 @@ class MainApp:
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self.contrast = None
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self.img_size = None
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self.img_size_old = 0 ## Check if the rendering size has changed, if it has the analysis has to be run
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self.img_size_old = 0 ## Check if the rendering size has changed, if it has the analysis has to be run
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self.sobel_select = None
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self.export_id = None
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self.brightness = None
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builder.import_variables(self,['canny_thr1','canny_thr2','img_path','contrast','img_size','sobel_select','export_id','brightness'])
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builder.import_variables(
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self,
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[
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"canny_thr1",
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"canny_thr2",
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"img_path",
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"contrast",
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"img_size",
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"sobel_select",
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"export_id",
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"brightness",
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],
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)
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builder.connect_callbacks(self)
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# Load values from config after UI has been initialised
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@ -68,22 +85,27 @@ class MainApp:
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self.img_size.set(config_json["size"])
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def on_quit(self, event=None):
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'''
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Close PLT windows on main app quit
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'''
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plt.close()
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self.mainwindow.quit();
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"""
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Close PLT windows on main app quit
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"""
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# TODO: This function runs multiple times for some reason
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if plt is not None:
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plt.close() # Close graph vies
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log.file.close() # Close log files
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self.mainwindow.quit() # Close main
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def run(self):
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'''
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Run loop
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'''
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"""
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Run loop
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"""
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self.mainwindow.mainloop()
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def img_prev(self, event=None):
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'''
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Open previous image from path
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'''
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"""
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Open previous image from path
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"""
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if self.img_current == 0:
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self.img_current = self.img_max - 1
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else:
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@ -91,9 +113,9 @@ class MainApp:
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self.update(self)
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def img_next(self, event=None):
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'''
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Open next image from path
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'''
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"""
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Open next image from path
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"""
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if self.img_current == (self.img_max - 1):
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self.img_current = 0
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else:
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@ -101,28 +123,28 @@ class MainApp:
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self.update(self)
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def apply(self, event=None, path=None):
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'''
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Export current dataset
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'''
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"""
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Export current dataset
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"""
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# Get export settings
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img_arr = self.tk_imgs
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img_id = self.export_id.get()
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if path == None:
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path = config_json["out"]
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else:
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print(F"Using path: {path}")
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print(f"Using path: {path}")
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if (img_id >= 0 and img_id < len(img_arr)):
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if img_id >= 0 and img_id < len(img_arr):
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# Create file
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now = datetime.datetime.now()
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new_file_name = F"{self.img_current}-{self.output[1][img_id]}-{now.strftime('%Y-%m-%dT%H.%M.%S')}.png"
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new_file_name = f"{self.img_current}-{self.output[1][img_id]}-{now.strftime('%Y-%m-%dT%H.%M.%S')}.png"
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# Put data
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file_path = pathlib.Path(path, new_file_name)
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# print(file_path)
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imgpil = ImageTk.getimage(self.tk_imgs[img_id])
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imgpil.save(file_path, "PNG" )
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imgpil.save(file_path, "PNG")
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imgpil.close()
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print(f"Exported Image ID {img_id} to {os.path.join(path, new_file_name)}")
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@ -130,31 +152,36 @@ class MainApp:
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print("Nothing to export!")
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def apply_all(self, event=None):
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'''
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Export given preprocess id for every image in the dataset folder
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'''
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"""
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Export given preprocess id for every image in the dataset folder
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"""
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img_id = self.export_id.get()
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img_current = copy.deepcopy(self.img_current)
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now = datetime.datetime.now()
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path = pathlib.Path(config_json["out"], F"{self.output[1][img_id]}-all-{now.strftime('%Y-%m-%dT%H.%M.%S')}/")
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path = pathlib.Path(
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config_json["out"],
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f"{self.output[1][img_id]}-all-{now.strftime('%Y-%m-%dT%H.%M.%S')}/",
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)
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os.mkdir(path)
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while True:
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self.img_next()
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self.update(part_update=True) # Enforce partial update since we don't need the histograms etc.
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self.update(
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part_update=True
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) # Enforce partial update since we don't need the histograms etc.
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self.apply(path=path)
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if (self.img_current == img_current):
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if self.img_current == img_current:
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break
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## Ensure display is always correct with image
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self.update()
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def add_output(self, data, name: str):
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'''
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Add CV2 image to canvas output
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'''
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"""
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Add CV2 image to canvas output
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"""
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self.output[0].append(data)
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self.output[1].append(name)
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@ -171,7 +198,7 @@ class MainApp:
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self.meta.config(state=NORMAL)
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self.meta.delete(1.0, END)
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self.meta.insert(END, f"{self.img_name[1]}\n")
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self.meta.insert(END, f"{self.img_name}\n")
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# Draw all output images
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for idx, data in enumerate(self.output[0]):
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@ -181,31 +208,29 @@ class MainApp:
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self.tk_imgs.append(tk_img)
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## Check if next item will be out of range
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if (drawX + size >= drawW):
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if drawX + size >= drawW:
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drawY += size
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drawX = 0
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self.canvas.configure(height=(drawY+size))
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self.canvas.configure(height=(drawY + size))
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self.canvas.create_image(drawX,drawY,anchor=NW,image=self.tk_imgs[idx],tags="og")
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self.canvas.create_image(
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drawX, drawY, anchor=NW, image=self.tk_imgs[idx], tags="og"
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)
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drawX += size
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# Add name to text box
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self.meta.insert(END, F"{idx}: {self.output[1][idx]}\n")
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self.meta.insert(END, f"{idx}: {self.output[1][idx]}\n")
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# Clear output
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self.meta.config(state=DISABLED)
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# Draw canvas
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# TODO IDK volgens mij moet je deze wel callen maar het programma doet het nog (geen vragen stellen)
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# self.canvas.draw()
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def createPlot(self, columns, rows):
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fig, axs = plt.subplots(columns, rows)
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return axs
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def drawHist(self, image, labels, column, row):
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self.axs[column, row].clear()
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for i,lab in enumerate(labels):
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for i, lab in enumerate(labels):
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hist = cv2.calcHist(
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[image],
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[i],
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@ -238,31 +263,61 @@ class MainApp:
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# print(f"Result at thres {th1}, {th2}; \tIndex {y_ind}, {x_ind} \t= {w_res}")
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# print(results[y_ind])
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func = np.diag(results)
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self.axs[column, row-1].clear()
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self.axs[column, row-1].title.set_text("Canny F U N C")
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self.axs[column, row-1].plot(func)
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self.axs[column, row-1].plot(np.diff(func))
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self.axs[column, row - 1].clear()
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self.axs[column, row - 1].title.set_text("Canny F U N C")
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self.axs[column, row - 1].plot(func)
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self.axs[column, row - 1].plot(np.diff(func))
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self.axs[column, row].title.set_text(F"Mean: {np.matrix(results).mean()}\nStd: {np.matrix(results).std()}")
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self.axs[column, row].title.set_text(
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f"Mean: {np.matrix(results).mean()}\nStd: {np.matrix(results).std()}"
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)
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self.axs[column, row].imshow(results)
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self.axs[column, row].xaxis.set_major_formatter(lambda x, pos: str(x*canny_step))
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self.axs[column, row].yaxis.set_major_formatter(lambda x, pos: str(x*canny_step))
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self.axs[column, row].xaxis.set_major_formatter(
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lambda x, pos: str(x * canny_step)
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)
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self.axs[column, row].yaxis.set_major_formatter(
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lambda x, pos: str(x * canny_step)
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)
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log.add("Canny Mean", np.matrix(results).mean())
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log.add("Canny Std", np.matrix(results).std())
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log.add("Canny Min", np.matrix(results).min())
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log.add("Canny Max", np.matrix(results).max())
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# log.add("Canny Diff max", np.diff(func))
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def writeStats(self, img, labels, column, row):
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mean, std = imgStats(img)
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self.axs[column, row].title.set_text(
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||||
"Mean: %c:%d %c:%d %c:%d \nStd: %c:%d %c:%d %c:%d"
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||||
%(labels[0], mean[0], labels[1], mean[1], labels[2], mean[2],
|
||||
labels[0], std[0], labels[1], std[1], labels[2], std[2]))
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% (
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labels[0],
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||||
mean[0],
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||||
labels[1],
|
||||
mean[1],
|
||||
labels[2],
|
||||
mean[2],
|
||||
labels[0],
|
||||
std[0],
|
||||
labels[1],
|
||||
std[1],
|
||||
labels[2],
|
||||
std[2],
|
||||
)
|
||||
)
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||||
|
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for idx, label in enumerate(labels):
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||||
log.add(f"Mean {label}", mean[idx])
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||||
log.add(f"Std {label}", std[idx])
|
||||
|
||||
def update(self, event=None, part_update=False):
|
||||
path = self.img_path.get()
|
||||
|
||||
## Check if hist and canny hm have to be rerendered
|
||||
if not part_update: ## If partial update has not been forced, check if full update is required
|
||||
if (self.img_current != self.img_old or self.img_size != self.img_size_old):
|
||||
if (
|
||||
not part_update
|
||||
): ## If partial update has not been forced, check if full update is required
|
||||
if self.img_current != self.img_old or self.img_size != self.img_size_old:
|
||||
part_update = False
|
||||
self.img_old = self.img_current
|
||||
self.img_size_old = self.img_size
|
||||
@ -281,7 +336,8 @@ class MainApp:
|
||||
images.append(file)
|
||||
|
||||
self.img_max = len(images)
|
||||
self.img_name = os.path.split(images[self.img_current])
|
||||
self.img_name = os.path.split(images[self.img_current])[1]
|
||||
log.add("Img", self.img_name)
|
||||
|
||||
# Get all user vars
|
||||
ct1 = self.canny_thr1.get()
|
||||
@ -296,7 +352,7 @@ class MainApp:
|
||||
|
||||
# Import and resize image
|
||||
img = cv2.imread(images[self.img_current])
|
||||
img = cv2.resize(img, (size, size), interpolation = cv2.INTER_AREA)
|
||||
img = cv2.resize(img, (size, size), interpolation=cv2.INTER_AREA)
|
||||
self.add_output(img, "Original")
|
||||
|
||||
# Set grayscale
|
||||
@ -306,34 +362,39 @@ class MainApp:
|
||||
# Contrast / brightness boost
|
||||
contrast_val = contrast / 100
|
||||
bright_val = bright / 100
|
||||
img_contrast = np.clip(contrast_val * (img_gray + bright_val), 0, 255).astype(np.uint8)
|
||||
img_contrast = np.clip(
|
||||
contrast_val * (img_gray + bright_val), 0, 255
|
||||
).astype(np.uint8)
|
||||
# self.add_output(img_contrast, F"Contrast / Brightness\n c+{contrast_val} b+{bright_val}")
|
||||
self.add_output(img_contrast, F"BCG")
|
||||
self.add_output(img_contrast, f"BCG")
|
||||
|
||||
# Blurred edition
|
||||
img_blur = cv2.GaussianBlur(img_gray, (3, 3), 0)
|
||||
self.add_output(img_blur, "Blurred_k3")
|
||||
|
||||
# Sobel edge
|
||||
if sxy in ['x', 'y', 'both']:
|
||||
if sxy == 'x':
|
||||
if sxy in ["x", "y", "both"]:
|
||||
if sxy == "x":
|
||||
dx = 1
|
||||
dy = 0
|
||||
elif sxy == 'y':
|
||||
elif sxy == "y":
|
||||
dx = 0
|
||||
dy = 1
|
||||
elif sxy == 'both':
|
||||
elif sxy == "both":
|
||||
dx = 1
|
||||
dy = 1
|
||||
|
||||
img_sobel = cv2.Sobel(src=img_blur, ddepth=cv2.CV_8U, dx=dx, dy=dy, ksize=5)
|
||||
img_sobel = cv2.Sobel(
|
||||
src=img_blur, ddepth=cv2.CV_8U, dx=dx, dy=dy, ksize=5
|
||||
)
|
||||
else:
|
||||
img_sobel = img_gray
|
||||
|
||||
self.add_output(img_sobel, "Sobel_edge")
|
||||
# self.add_output(img_sobel, F"Sobel Edge\n nz={cv2.countNonZero(img_sobel)}")
|
||||
log.add("Sobel nonzero", cv2.countNonZero(img_sobel))
|
||||
|
||||
# Canny edge
|
||||
img_canny = cv2.Canny(image=img_blur,threshold1=ct1,threshold2=ct2)
|
||||
img_canny = cv2.Canny(image=img_blur, threshold1=ct1, threshold2=ct2)
|
||||
self.add_output(img_canny, "Canny_edge")
|
||||
|
||||
# BGR
|
||||
@ -342,29 +403,34 @@ class MainApp:
|
||||
self.add_output(img[:, :, 2], "BGR_R")
|
||||
|
||||
if img is not None:
|
||||
self.drawHist(img, ('B', 'G', 'R'), 0, 0)
|
||||
self.writeStats(img, ('B', 'G', 'R'), 0, 0)
|
||||
self.drawHist(img, ("B", "G", "R"), 0, 0)
|
||||
self.writeStats(img, ("B", "G", "R"), 0, 0)
|
||||
|
||||
# HSV
|
||||
img_hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
|
||||
self.add_output(img_hsv, "HSV")
|
||||
self.add_output(img_hsv[:, :, 0], "HSV_H") # H
|
||||
self.add_output(img_hsv[:, :, 1], "HSV_S") # S
|
||||
self.add_output(img_hsv[:, :, 2], "HSV_V") # V
|
||||
self.add_output(img_hsv[:, :, 0], "HSV_H") # H
|
||||
self.add_output(img_hsv[:, :, 1], "HSV_S") # S
|
||||
self.add_output(img_hsv[:, :, 2], "HSV_V") # V
|
||||
|
||||
if not part_update:
|
||||
if img_hsv is not None:
|
||||
self.drawHist(img_hsv, ('H', 'S', 'V'), 0, 1)
|
||||
self.writeStats(img_hsv, ('H', 'S', 'V'), 0, 1)
|
||||
self.drawHist(img_hsv, ("H", "S", "V"), 0, 1)
|
||||
self.writeStats(img_hsv, ("H", "S", "V"), 0, 1)
|
||||
|
||||
# Canny Heatmap
|
||||
if not part_update:
|
||||
self.drawCannyHM(img, 1, 1)
|
||||
|
||||
# Write results to CSV file
|
||||
if not part_update:
|
||||
log.update()
|
||||
|
||||
# Show all data
|
||||
plt.show(block=False) ## Graphs
|
||||
plt.show(block=False) ## Graphs
|
||||
self.draw_output(size) ## Images
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
app = MainApp()
|
||||
app.run()
|
||||
|
||||
Loading…
Reference in New Issue
Block a user