Update detect_with_embedding.sh

detect_with_embedding.sh

@@ -1,8 +1,8 @@
 #!/bin/bash
 
 # Define base directory, Python script, and input directory
-BASE_DIR="$HOME/exp/sylbreak4all/lang_detection/embedding"
-PYTHON_SCRIPT="$BASE_DIR/embed_lang_detect.py"  # Replace with the name of your Python script
+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"
@@ -14,14 +14,14 @@ run_detection() {
     echo "Running language detection using $model_type models..."
     for file in "$INPUT_DIR"/*; do
         filename=$(basename -- "$file")
-        detected_language=$(python3 "$PYTHON_SCRIPT" --mode detect --input "$file" --model_folder "$model_dir")
+        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 "$PYTHON_SCRIPT" --mode detect --input "$random_sentence" --model_folder "$model_dir")
+            detected_language_sentence=$(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 ""
@@ -29,10 +29,10 @@ run_detection() {
 }
 
 # Run detection using Word2Vec models
-run_detection "Word2Vec" "$WORD2VEC_DIR"
+run_detection "word2vec" "$WORD2VEC_DIR"
 
 # Run detection using FastText models
-run_detection "FastText" "$FASTTEXT_DIR"
+run_detection "fasttext" "$FASTTEXT_DIR"
 
 echo "Language detection completed for all files."