149 lines
8.9 KiB
Python
149 lines
8.9 KiB
Python
import numpy as np
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import pandas as pd
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from MIC2 import search_medicine_name, search_MIC_position, search_MIC, show_MIC, explain_MIC, \
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translation_medicine_name, search_interpretation_criteria, update_location
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def main_function(excel_drag, excel_standard, excel_ecv, input_image_path, output_image_path, fungus, bacteria,
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crop_x=200, crop_y=240, crop_width=500, crop_height=330, draw_width=260, draw_height=260):
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"""
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:param excel_drag: 路径，药敏板分布的 excel表格
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:param excel_standard: 路径，判断标准的 excel表格
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:param excel_ecv: 路径，折点信息的 excel表格
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:param input_image_path: 路径，待检验的药敏板图片
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:param output_image_path: 路径，初次标注后的药敏板图片
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:param fungus: string，菌属：珠菌属，隐球菌属，表示曲霉属
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:param bacteria: string，菌种，中文名
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:param crop_x: int，裁剪图片的 x值
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:param crop_y: int，裁剪图片的 y值
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:param crop_width: int，裁剪图片的宽度为 (图片的宽度 - crop_width)
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:param crop_height: int，裁剪图片的高度为 (图片的高度 - crop_height)
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:param draw_width: int，画框的宽度
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:param draw_height: int，画框的高度
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:return: medicine_name_list_chinese 药物的中文名字 [str, str, ..., str]
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medicine_name_list_english 药物的英文名字 [str, str, ..., str]
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show_MIC_list 展示的MIC信息 [str, str, ..., str]
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final_explain MIC对应的解释信息 [str, str, ..., str]
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MIC_position_list 初次拍照画框的位置 [(int, int), (int, int), ..., (int, int)]
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"""
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# --读取药敏板药品信息--
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drug_sensitivity_plate = pd.read_excel(excel_drag)
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drug_sensitivity_plate.drop(drug_sensitivity_plate.index[0], axis=0, inplace=True) # 删除第一行标题
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drug_sensitivity_plate.drop(drug_sensitivity_plate.columns[0], axis=1, inplace=True) # 删除第一列序号
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medicine_concentration = drug_sensitivity_plate.iloc[0:8, 0:12] # 得到 药品信息 + 浓度对应表
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medicine_information = drug_sensitivity_plate.iloc[:, 13:16] # 得到 药品名称 缩写 + 英文 + 中文 对应表
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# --找到药敏板中每一种药的名字（缩写）--
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medicine_name_list = search_medicine_name(medicine_concentration)
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# --找到药敏板药品对应的中文名字、英文名字--
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medicine_name_list_chinese, medicine_name_list_english = translation_medicine_name(medicine_information,
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medicine_name_list)
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# --找到菌属 + 药品对应的判读方法--
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interpretation_criteria = pd.read_excel(excel_standard)
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judge_standard = search_interpretation_criteria(interpretation_criteria, medicine_name_list_chinese, fungus)
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# --对应输入图片，根据不同菌属的判读方法，找到满足颜色需求的微孔，标记出来，保存下标记后的图片，并记下标记坐标--
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MIC_position_list = search_MIC_position(input_image_path, output_image_path, judge_standard,
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crop_x, crop_y, crop_width, crop_height,
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draw_width, draw_height)
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# --对应药敏板信息，找到对应药品的 MIC值--
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medicine_MIC_list = search_MIC(medicine_concentration, MIC_position_list)
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#--对应规则找到最后展示出来的 MIC信息--
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show_MIC_list = show_MIC(medicine_MIC_list, MIC_position_list)
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#--对应折点信息表，找到药品对应的 MIC解释信息，如果没有解释信息，返回"-1"，最后不解释--
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vertices_ecv = pd.read_excel(excel_ecv)
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final_explain = explain_MIC(vertices_ecv, fungus, bacteria, medicine_name_list_chinese, medicine_MIC_list)
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return medicine_name_list_chinese, medicine_name_list_english, show_MIC_list, final_explain, MIC_position_list
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# Todo: 输入像素位置，找到对应的组，然后替换掉坐标位置，加框，按照新的坐标重新找 MIC，最终显示的 MIC，解释信息
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def add_position(excel_drag, excel_ecv, input_image_path, output_image_path,
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location, location_list, fungus, bacteria,
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crop_x=200, crop_y=240, crop_width=500, crop_height=330, draw_width=260, draw_height=260):
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"""
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:param excel_drag: 路径，药敏板分布的 excel表格
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:param excel_ecv: 路径，折点信息的 excel表格
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:param input_image_path: 图片路径，已经经过标记过的图像
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:param output_image_path: 图片路径，手动点击添加框后的图像
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:param location: tuple，(height, width)，新加点的位置
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:param location_list: list, 原画框列表位置
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:param fungus: str, 菌属
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:param bacteria: str, 菌种
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:param crop_x: int，裁剪图片的 x值
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:param crop_y: int，裁剪图片的 y值
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:param crop_width: int，裁剪图片的宽度为 (图片的宽度 - crop_width)
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:param crop_height: int，裁剪图片的高度为 (图片的高度 - crop_height)
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:param draw_width: int，画框的宽度
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:param draw_height: int，画框的高度
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:return: medicine_name_list_chinese 药物的中文名字 [str, str, ..., str]
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medicine_name_list_english 药物的英文名字 [str, str, ..., str]
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show_MIC_list 新的展示的MIC信息 [str, str, ..., str]
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final_explain 新的MIC对应的解释信息 [str, str, ..., str]
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new_location_list 新的画框位置（同一组药品内计入新画框的位置）
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"""
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# --读取药敏板药品信息--
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drug_sensitivity_plate = pd.read_excel(excel_drag)
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drug_sensitivity_plate.drop(drug_sensitivity_plate.index[0], axis=0, inplace=True) # 删除第一行标题
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drug_sensitivity_plate.drop(drug_sensitivity_plate.columns[0], axis=1, inplace=True) # 删除第一列序号
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medicine_concentration = drug_sensitivity_plate.iloc[0:8, 0:12] # 得到 药品信息 + 浓度对应表
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medicine_information = drug_sensitivity_plate.iloc[:, 13:16] # 得到 药品名称 缩写 + 英文 + 中文 对应表
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# --找到药敏板中每一种药的名字（缩写）--
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medicine_name_list = search_medicine_name(drug_sensitivity_plate)
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# --找到药敏板药品对应的中文名字、英文名字--
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medicine_name_list_chinese, medicine_name_list_english = translation_medicine_name(medicine_information,
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medicine_name_list)
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#--更新位置--
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new_location_list = update_location(input_image_path, output_image_path, location, location_list,
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crop_x, crop_y, crop_width, crop_height, draw_width, draw_height)
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# --对应药敏板信息，找到对应药品的 MIC值--
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medicine_MIC_list = search_MIC(medicine_concentration, new_location_list)
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#--对应规则找到最后展示出来的 MIC信息--
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show_MIC_list = show_MIC(medicine_MIC_list, new_location_list)
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#--对应折点信息表，找到药品对应的 MIC解释信息，如果没有解释信息，返回"-1"，最后不解释--
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vertices_ecv = pd.read_excel(excel_ecv)
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final_explain = explain_MIC(vertices_ecv, fungus, bacteria, medicine_name_list_chinese, medicine_MIC_list)
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return medicine_name_list_chinese, medicine_name_list_english, show_MIC_list, final_explain, new_location_list
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if __name__ == '__main__':
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chinese_name, english_name, mic, explain, pos_li = main_function(
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"C:\\Users\\Liao\\Desktop\\MXK\\丹娜\\MIC\\药敏板药物信息示例\\药敏板药物信息示例.xlsx",
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"C:\\Users\\Liao\\Desktop\\MXK\\丹娜\\MIC\\药敏板药物信息示例\\药敏板药品判读规则表格.xlsx",
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"C:\\Users\\Liao\\Desktop\\MXK\\丹娜\\MIC\\药敏板药物信息示例\\MIC解释标准及ECV值.xlsx",
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"./data/念珠结果判读/2.jpg",
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"./data/res/test2_0.jpg",
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"隐球菌属",
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"新生隐球菌VNⅠ")
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print(chinese_name)
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print(english_name)
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print(mic)
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print(explain)
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print(pos_li)
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print("------新增框------")
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# 按照目前图片进行裁剪，可根据如下范围设定新加的孔在哪里
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# [200, 558, 916, 1274, 1632, 1990, 2348, 2706, 3064]
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# [240, 598, 956, 1314, 1672, 2030, 2388, 2746, 3104, 3462, 3820, 4178, 4536]
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# 比如(210, 250)就应该对应的是(1, 1)这个位置，(2780, 3900)对应的就是(8, 11)这个位置
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chinese_name_new, english_name_new, mic_new, explain_new, pos_new = add_position(
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"C:\\Users\\Liao\\Desktop\\MXK\\丹娜\\MIC\\药敏板药物信息示例\\药敏板药物信息示例.xlsx",
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"C:\\Users\\Liao\\Desktop\\MXK\\丹娜\\MIC\\药敏板药物信息示例\\MIC解释标准及ECV值.xlsx",
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"./data/res/test2_0.jpg",
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"./data/res/add_test2_0.jpg",
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(1500, 2500), pos_li,
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"隐球菌属",
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"新生隐球菌VNⅠ"
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)
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print(chinese_name_new)
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print(english_name_new)
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print(mic_new)
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print(explain_new)
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print(pos_new)
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