File size: 1,473 Bytes
0d84e21 aa61fae 0d84e21 aa61fae 0d84e21 aa61fae 0d84e21 aa61fae 0d84e21 aa61fae 0d84e21 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | #!/bin/bash
# Define base directory, Python script, and input directory
BASE_DIR="$HOME/exp/myNLP/lang_detect"
PYTHON_SCRIPT="$BASE_DIR/demo_usage.py" # Replace with the name of your Python script
INPUT_DIR="$BASE_DIR/data/eg_input"
WORD2VEC_DIR="$BASE_DIR/word2vec"
FASTTEXT_DIR="$BASE_DIR/fasttext"
# Function to run language detection
run_detection() {
model_type=$1
model_dir=$2
echo "Running language detection using $model_type models..."
for file in "$INPUT_DIR"/*; do
filename=$(basename -- "$file")
detected_language=$(python3 "$PYTHON_SCRIPT" --mode detect --approach $model_type --input "$file" --profiles "$model_dir")
echo "File: $filename - Detected Language with $model_type: $detected_language"
# Run detection on random sentences from the file, 10 times
for i in {1..10}; do
random_sentence=$(shuf -n 1 "$file")
echo "Attempt $i - Random sentence from $filename: $random_sentence"
detected_language_sentence=$(python3 "$PYTHON_SCRIPT" --mode detect --approach $model_type --input "$random_sentence" --profiles "$model_dir")
echo "Detected Language with $model_type: $detected_language_sentence"
done
echo ""
done
}
# Run detection using Word2Vec models
run_detection "word2vec" "$WORD2VEC_DIR"
# Run detection using FastText models
run_detection "fasttext" "$FASTTEXT_DIR"
echo "Language detection completed for all files."
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