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do_prediction*: pass arrays as float16 instead of float64 to TF

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Robert Sachunsky 2026-03-14 00:49:26 +01:00
parent 135064a48e
commit d6404dbbc2
1 changed files with 3 additions and 2 deletions
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5
src/eynollah/eynollah.py
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@ -485,7 +485,7 @@ class Eynollah:
list_y_d = [] list_y_d = []
batch_indexer = 0 batch_indexer = 0
img_patch = np.zeros((n_batch_inference, img_height_model, img_width_model, 3)) img_patch = np.zeros((n_batch_inference, img_height_model, img_width_model, 3), dtype=np.float16)
for i in range(nxf): for i in range(nxf):
for j in range(nyf): for j in range(nyf):
index_x_d = i * width_mid index_x_d = i * width_mid
@ -681,7 +681,7 @@ class Eynollah:
list_y_d = [] list_y_d = []
batch_indexer = 0 batch_indexer = 0
img_patch = np.zeros((n_batch_inference, img_height_model, img_width_model, 3)) img_patch = np.zeros((n_batch_inference, img_height_model, img_width_model, 3), dtype=np.float16)
for i in range(nxf): for i in range(nxf):
for j in range(nyf): for j in range(nyf):
index_x_d = i * width_mid index_x_d = i * width_mid
@ -810,6 +810,7 @@ class Eynollah:
self.logger.debug("enter do_prediction_new_concept (%s)", model.name) self.logger.debug("enter do_prediction_new_concept (%s)", model.name)
img = img / 255.0 img = img / 255.0
img = img.astype(np.float16)
prediction = model.predict(img[np.newaxis])[0] prediction = model.predict(img[np.newaxis])[0]
confidence = prediction[:, :, 1] confidence = prediction[:, :, 1]