EV5_Beeldherk_Bomen/src/suite.py

#!/usr/bin/python3
import pathlib
import pygubu
import glob
from tkinter import *
from PIL import ImageTk, Image
import numpy as np
import cv2
import time
import matplotlib.pyplot as plt
import json
from helpers.statistics import imgStats
import datetime 
import os
import copy

## UI config load
PROJECT_PATH = pathlib.Path(__file__).parent
PROJECT_UI = "./src/helpers/gui/main.ui"

## Config file load
CONFIG_PATH = "./src/config/config.json"
config_file = open(CONFIG_PATH)
config_json = json.load(config_file)

## UI class setup
class MainApp:
    def __init__(self, master=None):
        self.builder = builder = pygubu.Builder()
        builder.add_resource_path(PROJECT_PATH)
        builder.add_from_file(PROJECT_UI)
        
        # Main widget
        self.mainwindow = builder.get_object("main", master)

        # Canvas for output images
        self.canvas = builder.get_object("output_canvas")
        self.tk_imgs = [] # Required or python will forget 
        self.output = [[] for x in range(2)]
        self.meta = builder.get_object("dataset")

        # Keep track of images in dataset
        self.img_current = 0
        self.img_name = ""
        self.img_old = -1 ## minus 1 to enforce full update on start
        self.img_max = 0

        # Plots
        self.axs = self.createPlot(2, 2)

        # UI Variables
        self.canny_thr1 = None
        self.canny_thr2 = None
        self.img_path = None
        self.contrast = None
        
        self.img_size = None
        self.img_size_old = 0 ## Check if the rendering size has changed, if it has the analysis has to be run 
        
        self.sobel_select = None
        self.export_id = None
        self.brightness = None
        builder.import_variables(self,['canny_thr1','canny_thr2','img_path','contrast','img_size','sobel_select','export_id','brightness'])
        builder.connect_callbacks(self)
        
        # Load values from config after UI has been initialised
        self.img_path.set(config_json["path"])
        self.img_size.set(config_json["size"])

    def on_quit(self, event=None):
        '''
            Close PLT windows on main app quit
        '''
        plt.close()
        self.mainwindow.quit();

    def run(self):
        '''
            Run loop
        '''
        self.mainwindow.mainloop()
        
    def img_prev(self, event=None):
        '''
            Open previous image from path 
        '''
        if self.img_current == 0:
            self.img_current = self.img_max - 1
        else:
            self.img_current = self.img_current - 1
        self.update(self)

    def img_next(self, event=None):
        '''
            Open next image from path
        '''
        if self.img_current == (self.img_max - 1):
            self.img_current = 0
        else:
            self.img_current = self.img_current + 1
        self.update(self)

    def apply(self, event=None, path=None):
        '''
            Export current dataset
        '''
        # Get export settings
        img_arr = self.tk_imgs
        img_id = self.export_id.get()
        if path == None:
            path = config_json["out"]
        else:
            print(F"Using path: {path}")
        
        if (img_id >= 0 and img_id < len(img_arr)):            
            # Create file
            now = datetime.datetime.now()
            new_file_name = F"{self.img_current}-{self.output[1][img_id]}-{now.strftime('%Y-%m-%dT%H.%M.%S')}.png"
            
            # Put data
            file_path = pathlib.Path(path, new_file_name)
            # print(file_path)
            
            imgpil = ImageTk.getimage(self.tk_imgs[img_id])
            imgpil.save(file_path, "PNG" )
            imgpil.close()
            
            print(f"Exported Image ID {img_id} to {os.path.join(path, new_file_name)}")
        else:
            print("Nothing to export!")
            
    def apply_all(self, event=None):
        '''
            Export given preprocess id for every image in the dataset folder
        '''
        img_id = self.export_id.get()
        img_current = copy.deepcopy(self.img_current)
        
        now = datetime.datetime.now()
        path = pathlib.Path(config_json["out"], F"{self.output[1][img_id]}-all-{now.strftime('%Y-%m-%dT%H.%M.%S')}/")
        os.mkdir(path)
        
        while True:
            self.img_next()
            self.update(part_update=True) # Enforce partial update since we don't need the histograms etc. 
            self.apply(path=path)
            
            if (self.img_current == img_current):
                break

        ## Ensure display is always correct with image
        self.update()

    def add_output(self, data, name: str):
        '''
            Add CV2 image to canvas output
        '''
        self.output[0].append(data)
        self.output[1].append(name)
        
    def draw_output(self, size):
        # Check if size of canvas has updated
        drawW = self.canvas.winfo_width()
        
        # Reset drawing position
        drawX = 0
        drawY = 0
        
        # Clear previously printed images
        self.tk_imgs = []
        
        self.meta.config(state=NORMAL)
        self.meta.delete(1.0, END)
        self.meta.insert(END, f"{self.img_name[1]}\n")        
        
        # Draw all output images
        for idx, data in enumerate(self.output[0]):
            # Create ui image
            tk_img = cv2.cvtColor(data, cv2.COLOR_BGR2RGB)
            tk_img = ImageTk.PhotoImage(image=Image.fromarray(tk_img))
            self.tk_imgs.append(tk_img)
        
            ## Check if next item will be out of range
            if (drawX + size >= drawW):
                drawY += size
                drawX = 0
                self.canvas.configure(height=(drawY+size))
                
            self.canvas.create_image(drawX,drawY,anchor=NW,image=self.tk_imgs[idx],tags="og")
            drawX += size
            
            # Add name to text box
            self.meta.insert(END, F"{idx}: {self.output[1][idx]}\n")
            
        # Clear output
        self.meta.config(state=DISABLED)
        
        # Draw canvas
        # TODO IDK volgens mij moet je deze wel callen maar het programma doet het nog (geen vragen stellen)
        # self.canvas.draw()

    def createPlot(self, columns, rows):
        fig, axs = plt.subplots(columns, rows)
        return axs
    
    def drawHist(self, image, labels, column, row):
        self.axs[column, row].clear()
        for i,lab in enumerate(labels):
            hist = cv2.calcHist(
                [image],
                [i],
                None,
                [256],
                [0, 256],
            )
            self.axs[column, row].plot(hist, label=lab)
            self.axs[column, row].grid()
            self.axs[column, row].legend()
            
    def drawCannyHM(self, img, column, row):
        self.axs[column, row].clear()
        canny_max = 500
        canny_step = 20

        results = [[] for x in range((int)(canny_max / canny_step))]

        for th1 in range(0, canny_max, canny_step):
            for th2 in range(0, canny_max, canny_step):
                # Canny Edge Detection
                edges = cv2.Canny(image=img, threshold1=th1, threshold2=th2)
                
                w_res = cv2.countNonZero(edges)
                y_ind = (int)(th1 / canny_step)
                x_ind = (int)(th2 / canny_step)
                
                results[y_ind].append(w_res)
                
                # print(f"Result at thres {th1}, {th2}; \tIndex {y_ind}, {x_ind} \t= {w_res}")
                # print(results[y_ind])
                
                
        func = np.diag(results)
        self.axs[column, row-1].clear()
        self.axs[column, row-1].title.set_text("Canny F U N C")
        self.axs[column, row-1].plot(func)
        self.axs[column, row-1].plot(np.diff(func))
        
        self.axs[column, row].title.set_text(F"Mean: {np.matrix(results).mean()}\nStd: {np.matrix(results).std()}")
        self.axs[column, row].imshow(results)
        self.axs[column, row].xaxis.set_major_formatter(lambda x, pos: str(x*canny_step))
        self.axs[column, row].yaxis.set_major_formatter(lambda x, pos: str(x*canny_step))

    def writeStats(self, img, labels, column, row):
        mean, std = imgStats(img)
        self.axs[column, row].title.set_text(
            "Mean: %c:%d %c:%d %c:%d \nStd: %c:%d %c:%d %c:%d"
            %(labels[0], mean[0], labels[1], mean[1], labels[2], mean[2], 
                labels[0], std[0], labels[1], std[1], labels[2], std[2]))
    
    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):
                part_update = False
                self.img_old = self.img_current
                self.img_size_old = self.img_size
            else:
                part_update = True
        else:
            print("Partial update forced!")
        
        if path != None and path != "":
            # Get all images at current path
            images = []
            for file in glob.glob(path + "/*.jpg"):
                images.append(file)
                
            self.img_max = len(images)
            self.img_name = os.path.split(images[self.img_current])
                
            # Get all user vars
            ct1 = self.canny_thr1.get()
            ct2 = self.canny_thr2.get()            
            sxy = self.sobel_select.get()
            size = self.img_size.get()
            contrast = self.contrast.get()
            bright = self.brightness.get()
            
            # Clear output
            self.output = [[] for x in range(2)]
            
            # Import and resize image
            img = cv2.imread(images[self.img_current])
            img = cv2.resize(img, (size, size), interpolation = cv2.INTER_AREA)
            self.add_output(img, "Original")
            
            # Set grayscale
            img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
            self.add_output(img_gray, "Grayscale")
            
            # 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)
            # self.add_output(img_contrast, F"Contrast / Brightness\n   c+{contrast_val} b+{bright_val}")
            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':
                    dx = 1
                    dy = 0
                elif sxy == 'y':
                    dx = 0
                    dy = 1
                elif sxy == 'both':
                    dx = 1
                    dy = 1
                    
                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)}")
            
            # Canny edge
            img_canny = cv2.Canny(image=img_blur,threshold1=ct1,threshold2=ct2)
            self.add_output(img_canny, "Canny_edge")

            # BGR
            self.add_output(img[:, :, 0], "BGR_B")
            self.add_output(img[:, :, 1], "BGR_G")
            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)
            
            # 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
            
            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)
            
            # Canny Heatmap
            if not part_update:
                self.drawCannyHM(img, 1, 1)
            
            # Show all data
            plt.show(block=False)   ## Graphs
            self.draw_output(size)  ## Images

if __name__ == "__main__":
    app = MainApp()
    app.run()