Gabor Cselle
commited on
Commit
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db35ca2
1
Parent(s):
7987245
Added more fonts, bold and italics
Browse files- arrange_train_test_images.py +1 -1
- consts.py +23 -1
- train_font_identifier.py +0 -1
- visualize.ipynb +0 -0
arrange_train_test_images.py
CHANGED
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@@ -22,7 +22,7 @@ for font in fonts:
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os.makedirs(font_train_dir, exist_ok=True)
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os.makedirs(font_test_dir, exist_ok=True)
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font_files = [f for f in os.listdir(GEN_IMAGES_DIR) if f.startswith(font)]
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random.shuffle(font_files)
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train_files = font_files[:int(0.8 * len(font_files))]
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os.makedirs(font_train_dir, exist_ok=True)
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os.makedirs(font_test_dir, exist_ok=True)
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font_files = [f for f in os.listdir(GEN_IMAGES_DIR) if f.startswith(font + "_")]
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random.shuffle(font_files)
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train_files = font_files[:int(0.8 * len(font_files))]
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consts.py
CHANGED
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@@ -1,7 +1,29 @@
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# number of images to generate per font
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IMAGES_PER_FONT = 50
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# allowlist of fonts to use
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FONT_ALLOWLIST = ["Arial",
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# directory where to store the generated images
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GEN_IMAGES_DIR = './generated_images'
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# images organized into train and test directories
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# number of images to generate per font
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IMAGES_PER_FONT = 50
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# allowlist of fonts to use
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FONT_ALLOWLIST = ["Arial",
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"Arial Black",
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"Arial Bold Italic",
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"Arial Bold",
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"Avenir",
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"Courier",
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"Helvetica",
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"Georgia",
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"Tahoma",
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"Tahoma Bold",
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"Times New Roman",
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"Times New Roman Bold",
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"Times New Roman Italic",
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"Times New Roman Bold Italic",
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"Trebuchet MS",
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"Trebuchet MS Bold",
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"Trebuchet MS Italic",
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"Trebuchet MS Bold Italic",
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"Verdana",
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"Verdana Bold",
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"Verdana Italic",
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"Verdana Bold Italic"
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]
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# directory where to store the generated images
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GEN_IMAGES_DIR = './generated_images'
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# images organized into train and test directories
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train_font_identifier.py
CHANGED
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@@ -77,7 +77,6 @@ def validate(model, data_loader, criterion):
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print(image_datasets['train'].classes)
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-
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# Training loop with progress bar for epochs
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num_epochs = 10 # Replace with the number of epochs you'd like to train for
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for epoch in range(num_epochs):
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print(image_datasets['train'].classes)
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# Training loop with progress bar for epochs
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num_epochs = 10 # Replace with the number of epochs you'd like to train for
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for epoch in range(num_epochs):
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visualize.ipynb
CHANGED
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