248 lines
9.9 KiB
Python
248 lines
9.9 KiB
Python
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import simpleimageio as sio
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import figuregen
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from figuregen.util.templates import FullSizeWithCrops
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from figuregen.util.image import Cropbox
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import os
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import argparse
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import yaml
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import numpy as np
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class MyCrops(FullSizeWithCrops):
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def __init__(self, reference_image, method_images, crops,
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crops_below = True, method_names = None, use_latex = False,add=False):
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""" Shows a reference image next to a grid of crops from different methods.
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Args:
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reference_image: a reference image (or any other image to put full-size in the lefthand grid)
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method_images: list of images, each corresponds to a new column in the crop grid
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crops: list of crops to take from each method, each creates a new row and a marker on the reference
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crops_below: [optional] if False, the crops will be a column to the right of each image
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method_names: [optional] list of string, names for the reference and each method, to put above the crops
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use_latex: set to true to pretty-print captions with LaTeX commands (requires TikZ backend)
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Returns:
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A list of two grids:
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The first is a single image (reference), the second a series of crops, one or more for each method.
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"""
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self._reference_image = reference_image
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self._method_images = method_images
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self.use_latex = use_latex
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self._crops_below = crops_below
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self._errors = [
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self.compute_error(reference_image, m)
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for m in method_images
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]
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self._crop_errors = [
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[
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self.compute_error(crop.crop(reference_image), crop.crop(m))
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for m in method_images
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]
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for crop in crops
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]
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# Put in one list to make our life easier in the following
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images = [reference_image]
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images.extend(method_images)
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# Create the grid for the reference image
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self._ref_grid = [ figuregen.Grid(1, 1) for _ in range(len(images)) ]
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for i in range(len(images)):
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self._ref_grid[i][0, 0].image = self.tonemap(images[i])
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for crop in crops:
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self._ref_grid[i][0, 0].set_marker(crop.marker_pos, crop.marker_size, color=[255,255,255])
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# Create the grid with the crops
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if self._crops_below:
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self._crop_grid = [
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figuregen.Grid(num_cols=len(crops), num_rows=1)
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for _ in range(len(images))
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]
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for i in range(len(images)):
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for col in range(len(crops)):
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self._crop_grid[i][0, col].image = self.tonemap(crops[col].crop(images[i]))
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else:
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self._crop_grid = [
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figuregen.Grid(num_cols=1, num_rows=len(crops))
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for _ in range(len(images))
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]
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for i in range(len(images)):
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for row in range(len(crops)):
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self._crop_grid[i][row, 0].image = self.tonemap(crops[row].crop(images[i]))
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# Add padding to the right of all but the last image
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for i in range(len(images) - 1):
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self._ref_grid[i].layout.set_padding(right=1)
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self._crop_grid[i].layout.set_padding(right=1)
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if self._crops_below:
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self._ref_grid[i].layout.set_padding(bottom=1)
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if self._crops_below:
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self._ref_grid[-1].layout.set_padding(bottom=1)
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else:
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self._ref_grid[-1].layout.set_padding(right=1)
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# Put error values underneath the columns
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if self._crops_below:
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for i in range(len(images)):
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# if i > 0:
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# err = self.error_string(i - 1, self.errors)
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# else:
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# err = self.error_metric_name
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if add:
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self._crop_grid[i].set_title("bottom", method_names[i])
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self._crop_grid[i].layout.set_title("bottom", 6, 1, 8)
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else:
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pass # TODO
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# TODO this requires titles spanning multiple grids (the image and its crops)!
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# error_strings = [ f"{self.error_metric_name}" ]
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# error_strings.extend([ self.error_string(i, self.errors) for i in range(len(self.errors)) ])
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# self._crop_grid.set_col_titles("bottom", error_strings)
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# self._crop_grid.layout.set_padding(column=1, row=1)
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# self._crop_grid.layout.set_col_titles("bottom", fontsize=8, field_size_mm=2.8, offset_mm=0.5)
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# If given, show method names on top
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# TODO combine with error values, and always show both or neither
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# if method_names is not None:
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# self._crop_grid.set_col_titles("top", method_names)
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# self._crop_grid.layout.set_col_titles("top", fontsize=8, field_size_mm=2.8, offset_mm=0.25)
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# self._ref_grid.copy_layout(self._crop_grid)
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# self._ref_grid.layout.set_padding(right=1)
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# TODO set appropriate paddings for alignment etc
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def error_string(self, index, errors):
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""" Generates the human-readable error string for the i-th element in a list of error values.
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Args:
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index: index in the list of errors
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errors: list of error values, one per method, in order
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"""
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if self.use_latex and index == np.argmin(errors):
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return f""
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elif self.use_latex:
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return f""
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else:
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return f""
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def error_metric_name(self) -> str:
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return ""
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def main(data_root,image_file_1,image_file_2,image_file_3,dataset_type,ours_method,crops_1,crops_2,crops_3,width_cm,output_image,ours_method_1=None,ours_method_2=None,ours_method_3=None):
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data_root = os.path.join(data_root)
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original_image_1 = sio.read(os.path.join(data_root,"original",dataset_type,image_file_1))
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# 写完了你在这个里面直接运行就可以
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KinD_image_1= sio.read(os.path.join(data_root,"KinD",dataset_type,image_file_1))
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LIME_image_1= sio.read(os.path.join(data_root,"LIME",dataset_type,image_file_1))
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NPE_image_1 = sio.read(os.path.join(data_root,"NPE",dataset_type,image_file_1))
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SRIE_image_1 = sio.read(os.path.join(data_root,"SRIE",dataset_type,image_file_1))
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ZeroDCE_image_1 = sio.read(os.path.join(data_root,"ZeroDCE",dataset_type,image_file_1))
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ours_image_1 = sio.read(os.path.join(data_root,ours_method_1 if ours_method_1 else ours_method,dataset_type,image_file_1))
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original_image_2 = sio.read(os.path.join(data_root,"original",dataset_type,image_file_2))
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# 写完了你在这个里面直接运行就可以
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KinD_image_2= sio.read(os.path.join(data_root,"KinD",dataset_type,image_file_2))
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LIME_image_2= sio.read(os.path.join(data_root,"LIME",dataset_type,image_file_2))
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NPE_image_2 = sio.read(os.path.join(data_root,"NPE",dataset_type,image_file_2))
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SRIE_image_2 = sio.read(os.path.join(data_root,"SRIE",dataset_type,image_file_2))
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ZeroDCE_image_2 = sio.read(os.path.join(data_root,"ZeroDCE",dataset_type,image_file_2))
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ours_image_2 = sio.read(os.path.join(data_root,ours_method_2 if ours_method_2 else ours_method,dataset_type,image_file_2))
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original_image_3 = sio.read(os.path.join(data_root,"original",dataset_type,image_file_3))
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# 写完了你在这个里面直接运行就可以
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KinD_image_3= sio.read(os.path.join(data_root,"KinD",dataset_type,image_file_3))
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LIME_image_3= sio.read(os.path.join(data_root,"LIME",dataset_type,image_file_3))
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NPE_image_3 = sio.read(os.path.join(data_root,"NPE",dataset_type,image_file_3))
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SRIE_image_3 = sio.read(os.path.join(data_root,"SRIE",dataset_type,image_file_3))
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ZeroDCE_image_3 = sio.read(os.path.join(data_root,"ZeroDCE",dataset_type,image_file_3))
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ours_image_3 = sio.read(os.path.join(data_root,ours_method_3 if ours_method_3 else ours_method,dataset_type,image_file_3))
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output_image = os.path.abspath(output_image)
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figure_1 = MyCrops(
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reference_image=original_image_1,
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method_images=[
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KinD_image_1,
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LIME_image_1,
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NPE_image_1,
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SRIE_image_1,
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ZeroDCE_image_1,
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ours_image_1
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],
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crops=[
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Cropbox(top=crop[0], left=crop[1], height=crop[2], width=crop[3], scale=crop[4]) for crop in crops_1
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],
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# scene_name="Pool",
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method_names=["Reference", "KinD", "LIME", "NPE", "SRIE", "ZeroDCE", "Ours"],
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use_latex=True
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).figure
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figure_2 = MyCrops(
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reference_image=original_image_2,
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method_images=[
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KinD_image_2,
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LIME_image_2,
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NPE_image_2,
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SRIE_image_2,
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ZeroDCE_image_2,
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ours_image_2
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],
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crops=[
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Cropbox(top=crop[0], left=crop[1], height=crop[2], width=crop[3], scale=crop[4]) for crop in crops_2
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],
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# scene_name="Pool",
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method_names=["Reference", "KinD", "LIME", "NPE", "SRIE", "ZeroDCE", "Ours"],
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use_latex=True
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).figure
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figure_3=MyCrops(
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reference_image=original_image_3,
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method_images=[
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KinD_image_3,
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LIME_image_3,
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NPE_image_3,
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SRIE_image_3,
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ZeroDCE_image_3,
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ours_image_3
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],
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crops=[
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Cropbox(top=crop[0], left=crop[1], height=crop[2], width=crop[3], scale=crop[4]) for crop in crops_3
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],
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method_names=["Reference", "KinD", "LIME", "NPE", "SRIE", "ZeroDCE", "Ours"],
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use_latex=True,
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add=True
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).figure
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# scene_name="Pool",
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figuregen.figure([figure_1[0],figure_1[1],figure_2[0],figure_2[1],figure_3[0],figure_3[1]], width_cm=width_cm, filename=output_image)
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# grid = figuregen.Grid(3,1)
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# grid[0,0].set_image(figure)
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# grid[1,0].set_image(figure)
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# grid[2,0].set_image(figure)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument("--config", type=str, default="./config/compare3_1.yaml")
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args = parser.parse_args()
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with open(args.config, "r") as f:
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config = yaml.safe_load(f)
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main(**config)
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