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Commit f73a7bc1 authored by tomrink's avatar tomrink
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parent a364cf38
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...@@ -278,6 +278,7 @@ class SRCNN: ...@@ -278,6 +278,7 @@ class SRCNN:
self.test_labels = [] self.test_labels = []
self.test_preds = [] self.test_preds = []
self.test_probs = None self.test_probs = None
self.test_input = []
self.learningRateSchedule = None self.learningRateSchedule = None
self.num_data_samples = None self.num_data_samples = None
...@@ -342,7 +343,7 @@ class SRCNN: ...@@ -342,7 +343,7 @@ class SRCNN:
data_norm.append(lo[:, slc_y, slc_x]) data_norm.append(lo[:, slc_y, slc_x])
data_norm.append(hi[:, slc_y, slc_x]) data_norm.append(hi[:, slc_y, slc_x])
data_norm.append(avg[:, slc_y, slc_x]) data_norm.append(std[:, slc_y, slc_x])
# --------------------------------------------------- # ---------------------------------------------------
# If next uncommented, take out get_grid_cell_mean # If next uncommented, take out get_grid_cell_mean
# tmp = input_data[:, label_idx, :, :] # tmp = input_data[:, label_idx, :, :]
...@@ -580,6 +581,7 @@ class SRCNN: ...@@ -580,6 +581,7 @@ class SRCNN:
self.test_labels.append(labels) self.test_labels.append(labels)
self.test_preds.append(pred.numpy()) self.test_preds.append(pred.numpy())
self.test_input.append(inputs[:, :, :, 4])
self.test_loss(t_loss) self.test_loss(t_loss)
self.test_accuracy(labels, pred) self.test_accuracy(labels, pred)
...@@ -722,9 +724,10 @@ class SRCNN: ...@@ -722,9 +724,10 @@ class SRCNN:
labels = np.concatenate(self.test_labels) labels = np.concatenate(self.test_labels)
preds = np.concatenate(self.test_preds) preds = np.concatenate(self.test_preds)
inputs = np.concatenate(self.test_input)
print(labels.shape, preds.shape) print(labels.shape, preds.shape)
return labels, preds return labels, preds, inputs
def do_evaluate(self, inputs, ckpt_dir): def do_evaluate(self, inputs, ckpt_dir):
...@@ -775,10 +778,10 @@ class SRCNN: ...@@ -775,10 +778,10 @@ class SRCNN:
def run_restore_static(directory, ckpt_dir, out_file=None): def run_restore_static(directory, ckpt_dir, out_file=None):
nn = SRCNN() nn = SRCNN()
labels, preds = nn.run_restore(directory, ckpt_dir) labels, preds, inputs = nn.run_restore(directory, ckpt_dir)
if out_file is not None: if out_file is not None:
np.save(out_file, np.save(out_file,
[np.squeeze(labels), preds.argmax(axis=3)]) [np.squeeze(labels), preds.argmax(axis=3), np.squeeze(inputs)])
def run_evaluate_static(in_file, out_file, ckpt_dir): def run_evaluate_static(in_file, out_file, ckpt_dir):
...@@ -799,7 +802,8 @@ def run_evaluate_static(in_file, out_file, ckpt_dir): ...@@ -799,7 +802,8 @@ def run_evaluate_static(in_file, out_file, ckpt_dir):
refl_lo, refl_hi, refl_std, refl_avg = get_min_max_std(refl) refl_lo, refl_hi, refl_std, refl_avg = get_min_max_std(refl)
refl_lo = normalize(refl_lo, 'refl_0_65um_nom', mean_std_dct) refl_lo = normalize(refl_lo, 'refl_0_65um_nom', mean_std_dct)
refl_hi = normalize(refl_hi, 'refl_0_65um_nom', mean_std_dct) refl_hi = normalize(refl_hi, 'refl_0_65um_nom', mean_std_dct)
refl_avg = normalize(refl_avg, 'refl_0_65um_nom', mean_std_dct) #refl_avg = normalize(refl_avg, 'refl_0_65um_nom', mean_std_dct)
refl_avg = refl_std
refl_lo = np.squeeze(refl_lo) refl_lo = np.squeeze(refl_lo)
refl_hi = np.squeeze(refl_hi) refl_hi = np.squeeze(refl_hi)
refl_avg = np.squeeze(refl_avg) refl_avg = np.squeeze(refl_avg)
......
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