Merge branch 'master' into 'data_processing'

# Conflicts:
#   quality_check_gui.py

TODO.md

@@ -5,18 +5,26 @@
 
 Tasks related to the quality check algorithms.
 
-* [ ] automatically filter tiles without tissue
-    
+
+
+## Previews
+- [X] Put font file in resources directory
+- [x] Add checkbox to mark outlier pixels in preview
+    - Also save clean preview
+- [X] Save marked preview in preview directory
+
+
 ## GUI / UX
 
-* [ ] add default config file that is read when no `config.ini` exists
+* [X] add default config file that is read when no `config.ini` exists
     - push this default config to repo instead of specifig config    
-- [ ] implement a logging functionality
-- [ ] use separate GUI and logic threads to prevent stutter 
+- [X] implement a logging functionality
+- [X] use separate GUI and logic threads to prevent stutter 
 
 ## Technical
 - [ ] validate config input
 - [ ] add requirements.txt or setup.py
-- [ ] use default config file that is used when no config is found
+- [X] use default config file that is used when no config is found
 # DONE
-- [X] introduce pixel sampling quality check
\ No newline at end of file
+- [X] introduce pixel sampling quality check
+- [X] automatically filter tiles without tissue
\ No newline at end of file

analyze_section.py

@@ -51,3 +51,47 @@ def analyze_section(root_path, quality_check, on_tile_done=None):
                 on_tile_done(x, y, is_outlier, error_measure)
 
     return error_measure_matrix
+
+
+def analyze_section_with_coords(root_path, quality_check, on_tile_done=None):
+    """
+    Args:
+        root_path (str): Path of the root directory of the raw data
+        quality_check (QualityCheck): object of type SineCheck that defines an error measure for each tile.
+        on_tile_done (function(int, int, list)): Callback function. If passed, this function
+        will be called after every processed tile. The function will be called with the x- and
+        y-indices of the tile as int and a list that contains outlier image indices (or is empty).
+
+    Returns:
+        [np.array()]: 2d-array with dimensions corresponding to number of tiles. Each entry
+        of the 2d-array is a float with the error measure of the respective tile.
+        [np.array()]: TODO
+    """
+
+    # get last (alphabetic ordering) directory name in root_path to extract x- and y-dimension
+    directories = sorted([f for f in listdir(root_path) if isdir(join(root_path, f))])
+    last_dir = directories[-1]
+    xdim, ydim = last_dir.split("_")
+    # tiles are zero indexed
+    xdim, ydim = int(xdim) + 1, int(ydim) + 1
+
+    error_measure_matrix = np.zeros(shape=(xdim, ydim))
+    outlier_matrix = np.empty(shape=(xdim, ydim), dtype=object)
+    filtered_matrix = np.empty(shape=(xdim, ydim), dtype=object)
+    # iterate over each tile
+    for x in range(xdim):
+        for y in range(ydim):
+            # call analysis and save outlier indices
+            img_path = f"{root_path}/{str(x).zfill(2)}_{str(y).zfill(2)}/"
+            data = read_data(img_path)
+
+            error_measure, outlier_coords, filtered_coords = quality_check.calc_error_measure(data, return_coords=True)
+            error_measure_matrix[x, y] = error_measure
+            outlier_matrix[x, y] = outlier_coords
+            filtered_matrix[x, y] = filtered_coords
+            is_outlier = quality_check.threshold(error_measure)
+
+            if on_tile_done is not None:
+                on_tile_done(x, y, is_outlier, error_measure)
+
+    return error_measure_matrix, outlier_matrix, filtered_matrix

generate_preview.py

@@ -71,7 +71,7 @@ def generate_preview(tiff_path, overlap=0.28, scaling=None, image_index=0, origi
     # tiles are zero indexed
     nx, ny = int(xdim) + 1, int(ydim) + 1
 
-    if scaling is None:
+    if scaling is None or scaling == "":
         scaling = determine_scaling_factor(nx, ny, overlap)
 
     # resolution of cropped tile (without overlapping region)
@@ -126,7 +126,9 @@ def generate_preview(tiff_path, overlap=0.28, scaling=None, image_index=0, origi
 def insert_labels(preview, xdim, ydim):
     img = Image.fromarray(preview)
     draw = ImageDraw.Draw(img)
-    # font = ImageFont.truetype(config['PREVIEWS']['font_path'], 12)
+    preview_tile_x = preview.shape[0] / xdim
+    font = ImageFont.truetype('resources/DejaVuSans.ttf', int(preview_tile_x*0.08))
+    # TODO scale font with resolution
 
     # tile dimensions
     res_x = int(preview.shape[0] / xdim)
@@ -138,11 +140,77 @@ def insert_labels(preview, xdim, ydim):
             # should be black or white
             avgColor = np.mean(preview[x * res_x:x * res_x + 20, y * res_y:y * res_y + 20])
             # draw.text((y * res_y, x * res_x), f"{x:02d}_{y:02d}", fill=(255 if avgColor > 1000 else 0))
-            draw.text((y * res_y, x * res_x), f"{xdim - x - 1:02d}_{ydim - y - 1:02d}", (2**12 if avgColor < 1200 else 0))
+            draw.text((y * res_y, x * res_x), f"{xdim - x - 1:02d}_{ydim - y - 1:02d}",
+                      2 ** 12, font=font)  # if avgColor < 1200 else 0
 
     return np.asarray(img)
 
 
+def mark_preview(preview, matrix, outlier_coords, filtered_coords):
+    """
+    Draw outlier markings in a given preview image
+    Args:
+        preview: Preview image as array.
+        matrix: Error measure matrix with dimensions corresponding to number of tiles in x/y
+        outlier_coords: Coordinates of outlier pixels per tile (unscaled)
+        filtered_coords: Coordinates of filtered pixels per tile (unscaled)
+
+    Returns: Marked preview image as array.
+    """
+    preview = preview.copy()
+    overlap = 0.28
+    res_x, res_y = preview.shape[0] // matrix.shape[0], preview.shape[1] // matrix.shape[1]
+    # width to be used for red rectangles and pixel markings
+    width = int(res_x / min(matrix.shape) * 0.05 + 0.5)
+    idx = np.argwhere((matrix < 0.775) & (matrix != -1))
+
+    img = Image.fromarray(preview / 2 ** 4).convert('RGB')
+    draw = ImageDraw.Draw(img)
+    full_x, full_y = preview.shape
+
+    print(idx)
+    # mark outlier tiles with red square
+    for x, y in idx:
+        draw.rectangle([
+            full_y - (y + 1) * res_y,
+            full_x - (x + 1) * res_x,
+            full_y - y * res_y - 1,
+            full_x - x * res_x - 1], outline='red', width=width)
+
+    # mark coords
+    for x in range(matrix.shape[0]):
+        for y in range(matrix.shape[1]):
+            coords = filtered_coords[x, y]
+            for coord in coords:
+                # TODO respect overlap!
+                y_from = int(full_y - (y + 1) * res_y + coord[1]/tile_y * res_y + 0.5)
+                x_from = int(full_x - (x + 1) * res_x + coord[0]/tile_x * res_x + 0.5)
+                y_to = y_from + width
+                x_to = x_from + width
+
+                # print(f'draw rectangle from ({y_from, x_from}) to ({y_to, x_to})')
+                draw.rectangle([
+                    y_from, x_from, y_to, x_to
+                ], fill='blue')
+            coords = outlier_coords[x, y]
+            if matrix[x, y] == -1:
+                continue
+            # mark outliers with red filled squares
+            for coord in coords:
+                # TODO respect overlap!
+                y_from = int(full_y - (y + 1) * res_y + coord[0, 1]/tile_y * res_y + 0.5)
+                x_from = int(full_x - (x + 1) * res_x + coord[0, 0]/tile_x * res_x + 0.5)
+                y_to = y_from + width
+                x_to = x_from + width
+
+                # print(f'draw rectangle from ({y_from, x_from}) to ({y_to, x_to})')
+                draw.rectangle([
+                    y_from, x_from, y_to, x_to
+                ], fill='red')
+            # mark filtered coords with blue filled squares
+    return np.array(img)
+
+
 if __name__ == '__main__':
     def main():
         preview = generate_preview('/data/PLI-Group/Nils/stitching_minimal/')

gui_components.py

@@ -5,22 +5,83 @@ from tkinter import ttk
 from utils.read_config import config
 
 
+class ToolTip:
+    """
+    see
+    https://stackoverflow.com/questions/20399243/display-message-when-hovering-over-something-with-mouse-cursor-in-python
+    """
+    def __init__(self, widget):
+        self.widget = widget
+        self.tipwindow = None
+        self.id = None
+        self.text = None
+        self.x = self.y = 0
+
+    def showtip(self, text):
+        # Display text in tooltip window
+        self.text = text
+        if self.tipwindow or not self.text:
+            return
+        x, y, cx, cy = self.widget.bbox("insert")
+        x = x + self.widget.winfo_rootx() + 57
+        y = y + cy + self.widget.winfo_rooty() + 27
+        self.tipwindow = tw = tkinter.Toplevel(self.widget)
+        tw.wm_overrideredirect(1)
+        tw.wm_geometry("+%d+%d" % (x, y))
+        label = tkinter.Label(tw, text=self.text, justify=tkinter.LEFT,
+                              background="#ffffe0", relief=tkinter.SOLID, borderwidth=1,
+                              font=("tahoma", "8", "normal"))
+        label.pack(ipadx=1)
+
+    def hidetip(self):
+        tw = self.tipwindow
+        self.tipwindow = None
+        if tw:
+            tw.destroy()
+
+
+def add_tooltip(widget, text):
+    toolTip = ToolTip(widget)
+
+    def enter(event):
+        toolTip.showtip(text)
+
+    def leave(event):
+        toolTip.hidetip()
+
+    widget.bind('<Enter>', enter)
+    widget.bind('<Leave>', leave)
+
+
 class PreviewOptions(tkinter.LabelFrame):
     def __init__(self, master):
         super().__init__(master=master, text='Preview generation')
         # add the state variable to master frame for ease of access
         master.preview_state = tkinter.IntVar()
         master.preview_state.set(1)
+        master.mark_outliers_state = tkinter.IntVar()
+        master.mark_outliers_state.set(0)
         self.chk_preview = tkinter.Checkbutton(self, text=' Generate preview', variable=master.preview_state)
+        self.chk_mark_outliers = tkinter.Checkbutton(self, text=' Mark outliers', variable=master.mark_outliers_state)
 
         master.overlap = tkinter.StringVar()
         master.overlap.set('0.28')
+        master.scaling = tkinter.StringVar()
+        master.scaling.set('')
         self.overlap_label = tkinter.Label(self, text='Overlap: ')
         self.overlap_entry = tkinter.Entry(self, textvariable=master.overlap)
+        self.scaling_label = tkinter.Label(self, text='Scaling factor: ')
+        self.scaling_entry = tkinter.Entry(self, textvariable=master.scaling)
+
+        add_tooltip(self.scaling_label, 'use automatic scaling factor if left empty')
+        add_tooltip(self.scaling_entry, 'use automatic scaling factor if left empty')
 
-        self.chk_preview.grid(row=0, column=0)
-        self.overlap_label.grid(row=1, column=0)
-        self.overlap_entry.grid(row=1, column=1)
+        self.chk_preview.grid(row=0, column=0, sticky='W')
+        self.chk_mark_outliers.grid(row=1, column=0, sticky='W')
+        self.overlap_label.grid(row=2, column=0)
+        self.overlap_entry.grid(row=2, column=1)
+        self.scaling_label.grid(row=3, column=0)
+        self.scaling_entry.grid(row=3, column=1)
 
 
 class QualityCheckOptions(tkinter.LabelFrame):
@@ -41,8 +102,9 @@ class QualityCheckOptions(tkinter.LabelFrame):
         self.dropdown = ttk.OptionMenu(self, master.dropdown_state, options[2], *options)
 
         self.chk_quality.grid(row=0, column=0)
-        self.method_label.grid(row=1, column=0)
-        self.dropdown.grid(row=1, column=1)
+        if config.getboolean('GUI', 'debug'):
+            self.method_label.grid(row=1, column=0)
+            self.dropdown.grid(row=1, column=1)
 
 
 class DirectoryChooser(tkinter.Frame):
@@ -127,4 +189,4 @@ class GUI(tkinter.Frame):
 
         if severity != 'debug':
             self.result_text.insert('end', msg + '\n')
-            self.result_text.see(tkinter.END)
\ No newline at end of file
+            self.result_text.see(tkinter.END)

qchecks/sine_check.py

@@ -43,7 +43,6 @@ def get_samples_grid(data, num=400):
     """
     dim = data.shape[1:]
     stack = np.zeros((num, data.shape[0]))
-
     grid_length = int(np.sqrt(num))
     for y in range(grid_length):
         for x in range(grid_length):
@@ -59,6 +58,33 @@ def get_samples_grid(data, num=400):
     return stack
 
 
+def get_samples_grid_coords(data, num=400):
+    """
+        Get samples that are evenly distributed over picture.
+    """
+    dim = data.shape[1:]
+    stack = np.zeros((num, data.shape[0]))
+    coords = []
+    grid_length = int(np.sqrt(num))
+    for y in range(grid_length):
+        for x in range(grid_length):
+            stack[y * grid_length + x, :] = data[:,
+                                                 y * dim[0] // grid_length + dim[0] % grid_length,
+                                                 x * dim[1] // grid_length + dim[1] % grid_length]
+            coords.append((y * dim[0] // grid_length + dim[0] % grid_length,
+                           x * dim[1] // grid_length + dim[1] % grid_length))
+
+    # sample remainder randomly
+    for i in range(grid_length ** 2, num):
+        rand_x, rand_y = np.random.randint(0, data.shape[1]), np.random.randint(0, data.shape[2])
+        stack[i, :] = data[:, rand_x, rand_y]
+
+        coords.append((rand_y,
+                       rand_x))
+
+    return stack, np.array(coords)
+
+
 def get_samples_random(data, num=1):
     dims = data.shape[1:]
     stack = np.zeros((num, data.shape[0]))
@@ -110,23 +136,22 @@ class SineCheck(QualityCheck):
         self.measure_func = measure_func
         self.threshold_func = threshold_func
 
-    def calc_error_measure(self, data, debug_plot=False):
+    def calc_error_measure(self, data, return_coords=False, debug_plot=False):
         """
          For a given tile data (image stack) calculate an error measure that represents
             how well the signal of each pixel over the image stack corresponds to a sine signal.
         Args:
             data: tile data (shape=(n, y_dim, x_dim))
+            return_coords (bool): return indices of outlier pixels for this tile in addition to error measure if set
+                                  to True.
             debug_plot: bool for debugging purposes, if set to True display each sine fit along with the datapoints.
         Returns:
             Aggregated error measure (e.g. mean of all sine fit errors). This function also returns -1 if more than 30%
             of fits had to be discarded because the signal was too weak.
         """
-
+        filtered_coords = []  # samples that have been ignored due to weakness of signal
         errors = []
-        samples = get_samples_grid(data, num=self.num)
-
-        # number of samples that have been ignored due to weakness of signal
-        filtered_counter = 0
+        samples, coords = get_samples_grid_coords(data, num=self.num)
 
         for i, sample in enumerate(samples):
             try:
@@ -138,22 +163,32 @@ class SineCheck(QualityCheck):
             if fit.amplitude < 10:
                 # too much noise / not enough refraction
                 # ignore this sample
-                filtered_counter += 1
+                filtered_coords.append(coords[i])
                 continue
             if fit.mean > 2000:
                 # very bright, likely to be outside of tissue
                 # ignore this sample
-                filtered_counter += 1
+                filtered_coords.append(coords[i])
                 continue
 
             error = self.measure_func(sample, fit)
             errors.append(error)
 
-        if filtered_counter / self.num > 0.775:
-            # more than 75% of samples ignored, unable to judge this tile
-            return -1
+        errors = np.array(errors)
+        if return_coords:
+            idx = np.argwhere(errors < 0.7)
+            outlier_coords = coords[idx]
+            if len(filtered_coords) / self.num > 0.775:
+                # more than 75% of samples ignored, unable to judge this tile
+                return -1, outlier_coords, filtered_coords
+            else:
+                return self.aggregate_func(errors), outlier_coords, filtered_coords
         else:
-            return self.aggregate_func(np.array(errors))
+            if len(filtered_coords) / self.num > 0.775:
+                # more than 75% of samples ignored, unable to judge this tile
+                return -1
+            else:
+                return self.aggregate_func(errors)
 
     def threshold(self, error_measure):
         if error_measure == -1:  # unable to evaluate

quality_check_gui.py

@@ -6,6 +6,7 @@ from datetime import datetime
 from os import listdir
 from os.path import isdir
 import logging
+import threading
 
 import numpy as np
 import matplotlib.pyplot as plt
@@ -13,9 +14,10 @@ import wx
 from dateutil.tz import tzlocal
 from wx.lib.agw.multidirdialog import (DD_DIR_MUST_EXIST, DD_MULTIPLE,
                                        MultiDirDialog)
+from PIL import Image
 
-from analyze_section import analyze_section
-from generate_preview import IndexOrigin, generate_preview
+from analyze_section import analyze_section, analyze_section_with_coords
+from generate_preview import IndexOrigin, generate_preview, mark_preview
 from utils.upload_log import upload_log
 from gui_components import GUI
 from qchecks.zero_check import ZeroCheck
@@ -23,8 +25,8 @@ from qchecks.sine_check import SineCheck
 from qchecks.sine_measures import r2_measure
 from utils.read_config import config
 
-__version__ = '0.1.1'
-__revision_date = '09.06.2020'
+__version__ = '0.1.3'
+__revision_date = '28.07.2020'
 
 
 # TODO add file with python dependencies, especially opencv and wxpython, maybe add error handling if these libraries
@@ -92,47 +94,62 @@ def get_logger_filename(dir_name):
 def clicked_start(frame):
     entry = frame.dir_frame.tiff_path.get()
 
-    for path in entry.split(';'):
-        norm = os.path.normpath(path)
-        # identify the section that is being analysed by its directory name
-        dir_name = norm.split(os.sep)[-2]
-
-        path = check_directory(path, frame)
-        if not path:
-            # invalid directory
-            continue
-
-        if frame.preview_state.get():  # generate previews
-            frame.progress_text.set(f'{dir_name}: Generating preview..')
-            frame.update()
-            try:
-                process_preview_gen(frame, path)
-            except ValueError as e:
-                frame.print('Invalid preview resolution provided, see config file "config.ini".')
-
-        # init logger
-        logger_path = get_logger_filename(dir_name)
-        frame.logger = logging.getLogger()
-        logging.basicConfig(level=logging.INFO, )
-        fh = logging.FileHandler(logger_path)
-        fh.setLevel(logging.DEBUG)
-        frame.logger.addHandler(fh)
-
-        if frame.quality_state.get():  # run quality check
-            frame.progress_text.set(f'{dir_name}: Running quality check..')
-            frame.update()
-            process_quality_check(frame, path, logger_path)
-
-    frame.progress_text.set('Done!')
-
-
-def save_preview(preview, frame, tiff_path):
+    def logic_thread_task():
+        preview = None
+        for directory_entry in entry.split(';'):
+            paths = check_directory(directory_entry, frame)
+            if not paths:
+                # invalid directory
+                continue
+            for path in paths:
+                norm = os.path.normpath(path)
+                # identify the section that is being analysed by its directory name
+                dir_name = norm.split(os.sep)[-2]
+
+                frame.print(f'--- {dir_name} ---\n')
+
+                if frame.preview_state.get():  # generate previews
+                    frame.progress_text.set(f'{dir_name}: Generating preview..')
+                    frame.update()
+                    try:
+                        preview = process_preview_gen(frame, path)
+                    except ValueError as e:
+                        frame.print('Invalid preview resolution provided, see config file "config.ini".')
+
+                # init logger
+                log_path = get_logger_filename(dir_name)
+
+                frame.logger = logging.getLogger()
+                logging.basicConfig(level=logging.INFO, )
+                fh = logging.FileHandler(log_path)
+                fh.setLevel(logging.DEBUG)
+                frame.logger.addHandler(fh)
+
+                if frame.quality_state.get():  # run quality check
+                    frame.progress_text.set(f'{dir_name}: Running quality check..')
+                    frame.print(f'Running quality check..')
+                    frame.update()
+                    error_matrix, outlier_coords, filtered_coords = process_quality_check(frame, path)
+                    frame.print(f'Saved logfile at "{log_path}".')
+
+                    if frame.mark_outliers_state.get():  # generate preview with marked outliers
+                        # TODO catch error when no preview was generated
+                        marked_preview = mark_preview(preview, error_matrix, outlier_coords, filtered_coords)
+                        norm = os.path.normpath(directory_entry)
+                        # identify the section that is being analysed by its directory name
+                        dir_name = norm.split(os.sep)[-2] + '_marked'
+                        save_preview(marked_preview, frame, dir_name)
+
+            frame.print(f'')
+        frame.progress_text.set('Done!')
+
+    threading.Thread(target=logic_thread_task).start()
+
+
+def save_preview(preview, frame, dir_name):
     preview_root = config['PREVIEWS']['preview_path']
     # save preview to a fixed path
     time_stamp = datetime.now(tzlocal()).strftime('%Y%m%d_%H-%M')
-    norm = os.path.normpath(tiff_path)
-    # identify the section that is being analysed by its directory name
-    dir_name = norm.split(os.sep)[-2]
     preview_path = f'{preview_root}/{dir_name}_{time_stamp}.png'
 
     # TODO ensure no file overrides happen
@@ -155,7 +172,7 @@ def process_preview_gen(frame, tiff_path):
         frame.progress["value"] = frame.progress["value"] + 1
         frame.progress.update()
 
-    # read overlap from gui
+    # read overlap from GUI
     overlap = frame.overlap.get()
     bad_overlap = False
     try:
@@ -167,17 +184,33 @@ def process_preview_gen(frame, tiff_path):
         frame.print(f'Invalid overlap provided, using default value {default_overlap}.')
         overlap = default_overlap
 
+    # read scaling factor from GUI
+    scaling = frame.scaling.get()
+    if not scaling == "":
+        bad_scaling = False
+        try:
+            scaling = float(scaling)
+        except ValueError:
+            bad_scaling = True
+
+        if bad_scaling or scaling <= 0:
+            frame.print(f'Invalid scaling factor provided, using automatic scaling.')
+            scaling = None
+
     # benchmark time
     time_pre = time.time()
 
-    preview = generate_preview(tiff_path, overlap=overlap, origin=IndexOrigin.BOTTOM_RIGHT,
+    preview = generate_preview(tiff_path, overlap=overlap, scaling=scaling, origin=IndexOrigin.BOTTOM_RIGHT,
                                on_tile_done=progressbar_callback, insert_index_labels=True)
 
     time_post = time.time()
-
     frame.print(f'Generated preview in {time_post - time_pre:.2f}s')
+    norm = os.path.normpath(tiff_path)
+    # identify the section that is being analysed by its directory name
+    dir_name = norm.split(os.sep)[-2]
+    save_preview(preview, frame, dir_name)
 
-    save_preview(preview, frame, tiff_path)
+    return preview
 
 
 def process_quality_check(frame, tiff_path, logger_path):
@@ -200,13 +233,13 @@ def process_quality_check(frame, tiff_path, logger_path):
 
         frame.progress.update()
 
+    outlier_coords = None
+    filtered_coords = None
     frame.progress["value"] = 0
 
     if tiff_path is None:
         tiff_path = frame.tiff_path.get()
 
-    frame.print(f"Analyzing section {tiff_path}")
-
     # determine method to be used based on drop down menu
     method_string = frame.dropdown_state.get()
 
@@ -233,8 +266,11 @@ def process_quality_check(frame, tiff_path, logger_path):
 
     # call the actual analysis method
     time_pre = time.time()
-    error_matrix = analyze_section(
-        tiff_path, quality_check, on_tile_done=progressbar_callback)
+    if frame.mark_outliers_state.get() == 1:
+        error_matrix, outlier_coords, filtered_coords = analyze_section_with_coords(tiff_path, quality_check, on_tile_done=progressbar_callback)
+    else:
+        error_matrix = analyze_section(
+            tiff_path, quality_check, on_tile_done=progressbar_callback)
 
     # save error matrix
     # use name of section as file name for matrix
@@ -270,6 +306,9 @@ def check_directory(tiff_path, frame):
         tiff_path = os.path.join(tiff_path, directories[0])
         directories = ([f for f in listdir(tiff_path) if isdir(os.path.join(tiff_path, f))])
 
+    # if there are multiple directories, return each one
+    # postpone check if every single subdirectory is valid
+
     if not directories or len(directories[-1].split("_")) != 2: