Mercurial > repos > bgruening > cp_track_objects
diff color_to_gray.py @ 0:644e5e32a83c draft
"planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools commit 35da2dcd86747c9bff138e100dbe08c6106f3780"
author | bgruening |
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date | Sat, 06 Feb 2021 10:03:00 +0000 |
parents | |
children | 1fd453cd757b |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/color_to_gray.py Sat Feb 06 10:03:00 2021 +0000 @@ -0,0 +1,159 @@ +#!/usr/bin/env python + +import argparse +import json + +from cp_common_functions import get_json_value +from cp_common_functions import get_pipeline_lines +from cp_common_functions import get_total_number_of_modules +from cp_common_functions import INDENTATION +from cp_common_functions import update_module_count +from cp_common_functions import write_pipeline + +MODULE_NAME = "ColorToGray" +OUTPUT_FILENAME = "output.cppipe" + + +def build_ctg_header(module_name, module_number): + """Creates the first line of a module given the name and module number""" + result = "|".join([f"{module_name}:[module_num:{module_number}", + "svn_version:\\'Unknown\\'", + "variable_revision_number:4", + "show_window:True", + "notes:\\x5B\\'Convert the color image to grayscale.\\'\\x5D", + "batch_state:array(\\x5B\\x5D, dtype=uint8)", + "enabled:True", + "wants_pause:False]\n"]) + return result + + +def build_main_block(input_params): + """Creates the main block of the CP pipeline with the parameters that don't depend on conditional choices""" + result = INDENTATION.join([f"{INDENTATION}Select the input image:{get_json_value(input_params,'name_input_image')}\n", + f"Conversion method:{get_json_value(input_params,'con_conversion_method.conversion_method')}\n", + f"Image type:{get_json_value(input_params,'con_conversion_method.con_image_type.image_type')}\n", + ]) + + conversion_method = get_json_value(input_params, 'con_conversion_method.conversion_method') + + image_type = get_json_value(input_params, 'con_conversion_method.con_image_type.image_type') + rgb_comb_name_out = "OrigGray" + combine_w_red = 1.0 + combine_w_green = 1.0 + combine_w_blue = 1.0 + + split_red = "Yes" + split_green = "Yes" + split_blue = "Yes" + red_output_name = "OrigRed" + green_output_name = "OrigGreen" + blue_output_name = "OrigBlue" + + split_hue = "Yes" + split_saturation = "Yes" + split_value = "Yes" + hue_output_name = "OrigHue" + saturation_output_name = "OrigSaturation" + value_output_name = "OrigValue" + + channel_count = 1 + if conversion_method == "Combine": + if image_type == "RGB" or image_type == "HSV": + rgb_comb_name_out = get_json_value(input_params, 'con_conversion_method.name_output_image') + combine_w_red = get_json_value(input_params, 'con_conversion_method.con_image_type.weight_red_channel') + combine_w_green = get_json_value(input_params, 'con_conversion_method.con_image_type.weight_green_channel') + combine_w_blue = get_json_value(input_params, 'con_conversion_method.con_image_type.weight_blue_channel') + elif conversion_method == "Split": + if image_type == "RGB": + split_red = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_red.yes_no') + red_output_name = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_red.name_output_image') + split_green = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_green.yes_no') + green_output_name = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_green.name_output_image') + split_blue = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_blue.yes_no') + blue_output_name = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_blue.name_output_image') + elif image_type == "HSV": + split_hue = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_hue.yes_no') + hue_output_name = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_hue.name_output_image') + split_saturation = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_saturation.yes_no') + saturation_output_name = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_saturation.name_output_image') + split_value = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_value.yes_no') + value_output_name = get_json_value(input_params, 'con_conversion_method.con_image_type.con_convert_value.name_output_image') + + result += INDENTATION.join( + [f"{INDENTATION}Name the output image:{rgb_comb_name_out}\n", + f"Relative weight of the red channel:{str(combine_w_red)}\n", + f"Relative weight of the green channel:{str(combine_w_green)}\n", + f"Relative weight of the blue channel:{str(combine_w_blue)}\n", + + f"Convert red to gray?:{split_red}\n", + f"Name the output image:{red_output_name}\n", + f"Convert green to gray?:{split_green}\n", + f"Name the output image:{green_output_name}\n", + f"Convert blue to gray?:{split_blue}\n", + f"Name the output image:{blue_output_name}\n", + + f"Convert hue to gray?:{split_hue}\n", + f"Name the output image:{hue_output_name}\n", + f"Convert saturation to gray?:{split_saturation}\n", + f"Name the output image:{saturation_output_name}\n", + f"Convert value to gray?:{split_value}\n", + f"Name the output image:{value_output_name}\n" + ]) + + channel_count = 1 + if image_type == "Channels": + channels = input_params['con_conversion_method']['con_image_type']['rpt_channel'] + channel_count = len(channels) + result += INDENTATION.join( + [f"{INDENTATION}Channel count:{channel_count}\n" + ]) + + for ch in channels: + rel_weight_ch = 1.0 + image_name = "Channel1" + if conversion_method == "Combine": + rel_weight_ch = get_json_value(ch, 'weight_of_channel') + else: + image_name = get_json_value(ch, 'image_name') + result += INDENTATION.join( + [f"{INDENTATION}Channel number:{get_json_value(ch,'channel_no')}\n", + f"Relative weight of the channel:{str(rel_weight_ch)}\n", + f"Image name:{image_name}\n" + ]) + else: + result += INDENTATION.join( + [f"{INDENTATION}Channel count:{channel_count}\n", + "Channel number:Red\\x3A 1\n", + "Relative weight of the channel:1.0\n", + "Image name:Channel1\n" + ]) + + return result + + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument( + '-p', '--pipeline', + help='CellProfiler pipeline' + ) + parser.add_argument( + '-i', '--inputs', + help='JSON inputs from Galaxy' + ) + args = parser.parse_args() + + pipeline_lines = get_pipeline_lines(args.pipeline) + inputs_galaxy = json.load(open(args.inputs, "r")) + + current_module_num = get_total_number_of_modules(pipeline_lines) + current_module_num += 1 + pipeline_lines = update_module_count(pipeline_lines, current_module_num) + + header_block = build_ctg_header(MODULE_NAME, current_module_num) + main_block = build_main_block(inputs_galaxy) + + module_pipeline = f"\n{header_block}{main_block}\n" + pipeline_lines.append(module_pipeline) + + write_pipeline(OUTPUT_FILENAME, pipeline_lines)