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DeepLabv3+: add logging
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1 changed files with 10 additions and 3 deletions
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@ -3,6 +3,7 @@
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# Required dataset: https://drive.google.com/uc?id=1B9A9UCJYMwTL4oBEo4RZfbMZMaZhKJaz [instance-level-human-parsing.zip]
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from datetime import datetime
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from loguru import logger
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import os
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import cv2
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@ -24,6 +25,10 @@ DIR_OUTPUT=f"output/{datetime.utcnow().date().isoformat()}_deeplabv3plus_TEST"
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os.makedirs(DIR_OUTPUT)
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logger.info("DeepLabv3+ TEST")
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logger.info(f"> DIR_OUTPUT {DIR_OUTPUT}")
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train_images = sorted(glob(os.path.join(DATA_DIR, "Images/*")))[:NUM_TRAIN_IMAGES]
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train_masks = sorted(glob(os.path.join(DATA_DIR, "Category_ids/*")))[:NUM_TRAIN_IMAGES]
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val_images = sorted(glob(os.path.join(DATA_DIR, "Images/*")))[
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@ -64,8 +69,8 @@ def data_generator(image_list, mask_list):
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train_dataset = data_generator(train_images, train_masks)
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val_dataset = data_generator(val_images, val_masks)
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print("Train Dataset:", train_dataset)
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print("Val Dataset:", val_dataset)
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logger.info("Train Dataset:", train_dataset)
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logger.info("Val Dataset:", val_dataset)
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# ███ ███ ██████ ██████ ███████ ██
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@ -156,7 +161,7 @@ model.compile(
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loss=loss,
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metrics=["accuracy"],
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)
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logger.info(">>> Beginning training")
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history = model.fit(train_dataset,
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validation_data=val_dataset,
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epochs=25,
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@ -167,6 +172,8 @@ history = model.fit(train_dataset,
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)
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],
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)
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logger.info(">>> Training complete")
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logger.info(">>> Plotting graphs")
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plt.plot(history.history["loss"])
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plt.title("Training Loss")
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