|
import tensorflow as tf
|
|
import matplotlib.pyplot as plt
|
|
import numpy as np
|
|
from keras.models import load_model
|
|
import os
|
|
from plot import plot
|
|
import openpyxl
|
|
from dataInput_creatMask import dataInput_creatMask_rgb
|
|
# ???
|
|
os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE"
|
|
|
|
input_folder_1 = 'C:/Users/DELL/Desktop/NTUT_project/rgb_test/ttt/'
|
|
model_where = './model/model_0501.h5'
|
|
|
|
folder_1_analyze_data = dataInput_creatMask_rgb(input_folder_1,model_where)
|
|
wb = openpyxl.load_workbook('avg.xlsx')
|
|
s1 = wb['工作表1']
|
|
|
|
if type(folder_1_analyze_data) is dict:
|
|
for i in range(np.size(folder_1_analyze_data["R_avg"])):
|
|
print(folder_1_analyze_data["R_avg"][i]["file_name"])
|
|
print(folder_1_analyze_data["R_avg"][i]["data"] - folder_1_analyze_data["G_B_avg"][i]["data"])
|
|
s1.cell(1,i+1).value = folder_1_analyze_data["R_avg"][i]["file_name"]
|
|
s1.cell(2,i+1).value = folder_1_analyze_data["R_avg"][i]["data"] - folder_1_analyze_data["G_B_avg"][i]["data"]
|
|
s1.cell(3,i+1).value = folder_1_analyze_data["r_minus_gb_avg_withoutmax"][i]["data"]
|
|
wb.save('test.xlsx')
|
|
else:
|
|
if type(folder_1_analyze_data) is str:
|
|
print(folder_1_analyze_data)
|