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trial_purifier.py
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trial_purifier.py
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import glob
import os
import sys
import tkinter as tk
from tkinter import messagebox
from xml.etree import ElementTree
import cv2
import numpy as np
import pandas as pd
from PIL import Image, ImageTk
from utils import annotator
FOLDER_PATH = 'purifier/folders.pkl'
def get_folders():
"""
read all trial folders and return a dataframe
:return: dataframe
"""
# get the list of all folders
folders_path = sorted(glob.glob("data/Original-data/belvedere/*"))
# Create a dic to hold number of invalid images per folder
f_dic = {}
for path in folders_path:
f_dic[path] = 0
# Get the invalid images
# invalid_images = glob.glob("data/Original-data/*/*/*.jpg_")
# loop over all invalid images and +1 to the folder
# for img in invalid_images:
# t = img.split("/")
# f_path = '/'.join(t[:-1])
# f_dic[f_path] += 1
# make a data frame from dic
# f_list = [[k, v] for k, v in f_dic.items()]
folder_df = pd.DataFrame(data=folders_path, columns=["folder"])
folder_df["checked"] = False
#
# folder_df = folder_df.sort_values(["invalids"], ascending=False)
# folder_df.reset_index(inplace=True)
folder_df.to_pickle(FOLDER_PATH)
for i, row in folder_df.iterrows():
print(row.folder)
return folder_df
def get_dataframe(_path):
"""
get a path and read images and labels (xmls) from current directory
:param _path: directory path
:return: a dataframe
"""
all_images = sorted(glob.glob(_path + "/*.bmp"))
all_xmls = sorted(glob.glob(_path + "/*.xml"))
data = []
for i, img in enumerate(all_images):
vals = read_xml(all_xmls[i])
# add image number to sort the dataframe based on it
name = img.split("/")[-1]
num = name.split(".")[0]
num = int(num[:-2])
data.append([img, vals[0], vals[1], vals[2], vals[3], vals[4], num])
df = pd.DataFrame(data=data, columns=["path", "xt", "yt", "wt", "ht", "angt", "num"])
df = df.sort_values(["num"])
df.reset_index(inplace=True)
df["status"] = 0
return df
def read_xml(xml_path):
e = ElementTree.parse(xml_path).getroot()
x = np.float32(e[0].text)
y = np.float32(e[1].text)
w = np.float32(e[2].text)
h = np.float32(e[3].text)
a = np.float32(e[4].text)
return [x, y, w, h, a]
def numpy2pil(np_array: np.ndarray) -> Image:
"""
convert an HxWx3 numpy array into an RGB Image
:param np_array: input numpy array
:return: A PIL Image object
"""
assert_mfg = "input shall be a HxWx3 ndarray"
assert isinstance(np_array, np.ndarray), assert_mfg
assert np.ndim(np_array) == 3, assert_mfg
assert np_array.shape[2] == 3, assert_mfg
img = Image.fromarray(np_array, 'RGB')
return img
class inspector_gui:
def __init__(self, master, data):
self.frame = tk.Frame(master)
self.frame.pack_propagate(0)
self.frame.pack(fill=tk.BOTH, expand=1)
# Folder index
self.f_idx = 0
self.folder_df = data
self.n_folders = len(data)
self.current_df = None
self.n_img = 0
self.current_df_dirty = False
# folder navigation
self.prev_folder_btn = tk.Button(self.frame, text="previous Folder", command=lambda: self.change_folder(-1))
self.prev_folder_btn.place(width=140, height=30, x=20, y=5)
self.path_lbl = tk.Label(self.frame, text="Image path: ", anchor=tk.CENTER)
self.path_lbl.place(width=380, height=20, x=200, y=5)
self.next_folder_btn = tk.Button(self.frame, text="next Folder", command=lambda: self.change_folder(1))
self.next_folder_btn.place(width=140, height=30, x=640, y=5)
# big labeled image
self.canvas = tk.Canvas(self.frame, width=576, height=576, bg="yellow")
self.canvas.place(width=576, height=576, x=12, y=40)
img = Image.open("0in.jpg")
self.photo = ImageTk.PhotoImage(img)
self.image_ref = self.canvas.create_image((288, 288), image=self.photo)
# thumbsnail image
self.canvas_s = tk.Canvas(self.frame, width=192, height=192)
self.canvas_s.place(width=192, height=192, x=596, y=40)
self.photo_s = ImageTk.PhotoImage(img)
self.image_refs = self.canvas_s.create_image((96, 96), image=self.photo_s)
self.pager_lbl = tk.Label(self.frame, text="0/1234", anchor=tk.CENTER)
self.pager_lbl.place(width=192, height=20, x=596, y=225)
self.status_lbl = tk.Label(self.frame, text="0", anchor=tk.CENTER, font=("Courier", 34))
self.status_lbl.place(width=192, height=40, x=596, y=255)
# true false buttons
self.incorrect_btn = tk.Button(self.frame, text="Incorrect (i)", bg="red", command=lambda: self.updateDF(2))
self.incorrect_btn.place(width=80, height=40, x=610, y=410)
self.correct_btn = tk.Button(self.frame, text="correct (c)", bg="green", command=lambda: self.updateDF(1))
self.correct_btn.place(width=80, height=40, x=700, y=410)
# back and forward buttons for images
self.backButton = tk.Button(self.frame, text="<- back", command=lambda: self.updateIndex(-1))
self.backButton.place(width=80, height=30, x=610, y=470)
self.nextButton = tk.Button(self.frame, text="next ->", command=lambda: self.updateIndex(1))
self.nextButton.place(width=80, height=30, x=700, y=470)
# capture image and save dataframe buttons
self.capture_btn = tk.Button(self.frame, text="Capture (p)", command=self.capture)
self.capture_btn.place(width=80, height=30, x=610, y=530)
self.save_btn = tk.Button(self.frame, text="save", command=self.saveDF)
self.save_btn.place(width=80, height=30, x=700, y=530)
# export and rename buttons
self.export_btn = tk.Button(self.frame, text="export path", command=self.exportPath)
self.export_btn.place(width=80, height=30, x=700, y=580)
self.rename_btn = tk.Button(self.frame, text="rename path", command=self.file_renamer)
self.rename_btn.place(width=80, height=30, x=610, y=580)
# bind events with keyboard
master.bind('<Left>', self.leftKey)
master.bind('<Right>', self.rightKey)
master.bind('i', self.enterKey)
master.bind('c', self.spaceKey)
master.bind('p', self.captureKey)
# select the first folder as start point
self.goto_folder(0)
def rightKey(self, event):
self.updateIndex(1)
def leftKey(self, event):
self.updateIndex(-1)
def spaceKey(self, event):
self.updateDF(1)
def enterKey(self, event):
self.updateDF(2)
def captureKey(self, event):
self.capture()
def findNextIndex(self):
"""
loop over dataframe and return an index with status 0
if not found, alert and return index= 0
:return:
"""
status_0 = self.current_df.index[self.current_df["status"] == 0].tolist()
status_0 = sorted(status_0)
if len(status_0) == 0:
status_1 = self.current_df.index[self.current_df["status"] == 1].tolist()
status_1 = sorted(status_1)
if len(status_1) == 0:
return self.goto_folder(1)
else:
return status_1[0]
else:
return status_0[0]
def capture(self):
row = self.current_df.iloc[self.img_index]
img = cv2.imread(row.path, cv2.IMREAD_GRAYSCALE)
truth = [row.xt, row.yt, row.wt, row.ht, row.angt]
# Update the labeled image
img = annotator((0, 250, 0), img, *truth) # Green
save_path = row.path.replace("/", "-")
cv2.imwrite("purifier/" + save_path, img)
def change_folder(self, val):
"""
update the folder index and clip it between 0 and n_folders
:param val: +1 go next, -1 go previous
:return: updated folder_idx
"""
if self.current_df_dirty:
res = messagebox.askquestion("Save Data", "Did you save the data?", icon='warning')
if res == 'no':
return
self.f_idx += val
self.f_idx = np.clip(self.f_idx, 0, self.n_folders - 1)
self.goto_folder(self.f_idx)
def goto_folder(self, idx):
"""
Get the path from folder data frame. We should check if the upcomming folder
has already a dataframe for its images. if not, create one.
:param idx: index of current folder to be shown
"""
# get the row of current path
row = self.folder_df.iloc[idx]
# check if dataframe is already exist
df_name = row.folder.replace("/", "_")
df_path = "purifier/" + df_name + ".pkl"
if os.path.exists(df_path):
self.current_df = pd.read_pickle(df_path)
else:
# read all images and labels in current directory
self.current_df = get_dataframe(row.folder)
# reset the image index
self.img_index = self.findNextIndex()
self.n_img = len(self.current_df)
# update the folder name label
new_text = "{0}".format(row.folder)
self.path_lbl.configure(text=new_text)
self.current_df_dirty = False
# finally update GUI with new data
self.updateGUI()
def exportPath(self):
"""
export path of images which flaged as incorrect
:return:
"""
incorrects = self.current_df[self.current_df.status == 2]
path_txt = []
# loop over rows and extract the paths
for i, row in incorrects.iterrows():
path_txt.append(row.path + "\n")
# save file
f_row = self.folder_df.iloc[self.f_idx]
export_path = f_row.folder + "/incorrects.txt"
open(export_path, mode='w').writelines(path_txt)
# corrects = self.df[self.df.status == 1]
# with open(CHECKED_PATH, mode='a') as f:
# for i, row in corrects.iterrows():
# path = row.trial + "/" + row.img_id + "\n"
# f.writelines(path)
messagebox.showinfo("Export path", "incorrect paths exported successfuly at {}".format(export_path))
def updateDF(self, val):
"""
update the status of current row and go to next image
:return:
"""
self.current_df.at[self.img_index, "status"] = val
r = self.current_df.iloc[self.img_index]
print("{0} has been marked as {1}".format(r.path, r.status))
self.current_df_dirty = True
self.updateIndex(1)
def saveDF(self):
"""
save incorrect labeled images into a file
:return:
"""
# get the row of current path
row = self.folder_df.iloc[self.f_idx]
# check if dataframe is already exist
df_name = row.folder.replace("/", "_")
df_path = "purifier/"+df_name+".pkl"
try:
self.current_df.to_pickle(df_path)
except IOError:
print("IO Error")
except RuntimeError:
print("RuntimeError")
except EOFError:
print("EOFError")
except OSError:
print("OSError")
except:
print("Unexpected error:", sys.exc_info()[0])
self.current_df_dirty = False
messagebox.showinfo("save data", "Data saved successfuly at {}".format(df_path))
def updateIndex(self, val):
"""
update the image index and clip between 0, len(n_img). finally update the GUI
:param val:
:return:
"""
self.img_index += val
self.img_index = np.clip(self.img_index, 0, self.n_img - 1)
self.updateGUI()
def updateGUI(self):
"""
update the GUI based on img_index
:return:
"""
row = self.current_df.iloc[self.img_index]
# update pager
new_text = "{0}/{1}".format(self.img_index + 1, self.n_img)
self.pager_lbl.configure(text=new_text)
# update status
self.status_lbl.configure(text=str(row.status))
# update image holder
# load image
file = row.path.split(".")[0]
file = file + ".bmp"
if row.status == 2:
img = cv2.imread(file, cv2.IMREAD_GRAYSCALE)
else:
img = cv2.imread(file, cv2.IMREAD_GRAYSCALE)
# update thumbnails before manipulation
s_img = np.asarray(img, dtype=np.uint8)
s_img = Image.fromarray(s_img, 'L')
self.photo_s = ImageTk.PhotoImage(image=s_img)
self.canvas_s.itemconfig(self.image_refs, image=self.photo_s)
# resize image 3x and put label on it
img = cv2.resize(img, (576, 576))
truth = [row.xt * 3, row.yt * 3, row.wt * 3, row.ht * 3, row.angt]
img = annotator((0, 250, 0), img, *truth) # Green
img = numpy2pil(img)
self.photo = ImageTk.PhotoImage(image=img)
self.canvas.itemconfig(self.image_ref, image=self.photo)
def file_renamer(self):
"""
get the file path of miss labeled data, and read the paths inside the file,
and rename the extension part to jpg_ and xml_
:param file_path: list of bad-labeled images
:return:
"""
f_row = self.folder_df.iloc[self.f_idx]
export_path = f_row.folder + "/incorrects.txt"
counter = 0
with open(export_path, mode='r') as f:
for line in f:
line = line.strip()
root = line.split(".")[0]
os.rename(root + ".jpg", root + ".jpg_")
xml = root.replace("in.", "gt.")
os.rename(xml + ".xml", xml + ".xml_")
counter += 1
messagebox.showinfo("rename", " {} images has been renamed".format(counter))
if __name__ == '__main__':
top = tk.Tk()
top.title('Label inspector')
top.geometry("800x620")
top.resizable(0, 0)
# check if folder dataframe already saved on disk
if os.path.exists(FOLDER_PATH):
fdf = pd.read_pickle(FOLDER_PATH)
else:
fdf = get_folders()
inspector = inspector_gui(top, fdf)
top.mainloop()