Commit
•
659a0c6
1
Parent(s):
463c439
update parameters
Browse files
model.py
CHANGED
@@ -9,7 +9,7 @@ from PIL import Image
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import torch
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import cv2
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from time import process_time
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-
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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model_recog = load_from_checkpoint("weights/parseq/last.ckpt").eval().to(device).float()
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@@ -29,6 +29,7 @@ def prediction(image_path):
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t_start = process_time()
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image = cv2.imread(image_path)
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image_original = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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transform_compose = albu.Compose([
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albu.Lambda(image=preprocessing_fn), albu.Resize(SHAPE_X, SHAPE_Y)
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])
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@@ -47,10 +48,10 @@ def prediction(image_path):
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p = model_recog(image).softmax(-1)
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pred, p = model_recog.tokenizer.decode(p)
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t_stop = process_time()
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-
t_process = t_stop - t_start
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print(f'{image_path}: {pred[0]}, {t_process} seconds')
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return img_vis, pred[0], t_process
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import torch
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import cv2
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from time import process_time
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+
import imutils
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device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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model_recog = load_from_checkpoint("weights/parseq/last.ckpt").eval().to(device).float()
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t_start = process_time()
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image = cv2.imread(image_path)
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image_original = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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image_original = imutils.resize(image_original, width=image_original.shape[1]//5)
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transform_compose = albu.Compose([
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albu.Lambda(image=preprocessing_fn), albu.Resize(SHAPE_X, SHAPE_Y)
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])
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p = model_recog(image).softmax(-1)
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pred, p = model_recog.tokenizer.decode(p)
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t_stop = process_time()
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t_process = (t_stop - t_start)/2
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print(f'{image_path}: {pred[0]}, {t_process} seconds')
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return img_vis, pred[0], t_process
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