NanjingForestryUniversity/supermachine--tomato-passion_fruit
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fix:修复一点小瑕疵

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TG 2024-06-27 09:38:57 +08:00
parent 0d10cf5d23
commit 606e5fbe7b
2 changed files with 2 additions and 2 deletions
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2
20240529RGBtest3/classifer.py
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@ -382,7 +382,7 @@ class Spec_predict(object):
'''
# 对数据进行切片，筛选谱段
#qt_test进行测试时如果读取的是（30，30，224）需要解开注释进行数据切片，筛选谱段
data_x = data_x[ :25, :, setting.selected_bands ]
# data_x = data_x[ :25, :, setting.selected_bands ]
# 将筛选后的数据重塑为二维数组，每行代表一个样本
data_x = data_x.reshape(-1, setting.n_spec_rows * setting.n_spec_cols * setting.n_spec_bands)
data_y = self.model.predict(data_x)

2
20240529RGBtest3/main.py
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@ -32,7 +32,7 @@ def main(is_debug=False):
print('系统初始化中...')
#模型预热
#与qt_test测试时需要注释掉预热，模型接收尺寸为（25，30，13），qt_test发送的数据为（30，30，224），需要对数据进行切片（classifer.py第385行）
# _ = detector.predict(np.ones((setting.n_spec_rows, setting.n_spec_cols, setting.n_spec_bands), dtype=np.uint16))
_ = detector.predict(np.ones((setting.n_spec_rows, setting.n_spec_cols, setting.n_spec_bands), dtype=np.uint16))
# _ = classifier.predict(np.ones((setting.n_rgb_rows, setting.n_rgb_cols, setting.n_rgb_bands), dtype=np.uint8))
# _, _, _, _, _ =dp.analyze_tomato(cv2.imread(str(setting.tomato_img_dir)))
# _, _, _, _, _ = dp.analyze_passion_fruit(cv2.imread(str(setting.passion_fruit_img_dir))