diff --git a/.gitignore b/.gitignore
index 3e952f0..0fcc7c9 100644
--- a/.gitignore
+++ b/.gitignore
@@ -139,3 +139,10 @@ cython_debug/
 
 # Generated docs
 *.pdf
+
+/dataset/wav/
+!/dataset/wav/.gitkeep
+/dataset/processed/
+!/dataset/processed/.gitkeep
+/dataset/manifest.csv
+/eval/
\ No newline at end of file
diff --git a/Dockerfile b/Dockerfile
index 51cce77..70e3216 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -17,4 +17,7 @@ RUN curl https://raw.githubusercontent.com/tensorflow/magenta/master/magenta/too
     sed 's/sudo //' -i /tmp/magenta-install.sh && \
     bash --login /tmp/magenta-install.sh
 
+# install fluidsynth for MIDI to WAV conversion
+RUN apt-get install fluidsynth fluid-soundfont-gm --no-install-recommends
+
 RUN echo "conda activate magenta" >> /root/.bashrc
diff --git a/README.md b/README.md
index 0be0dc9..acb8d0f 100644
--- a/README.md
+++ b/README.md
@@ -15,8 +15,34 @@ $ make image # wywołuje docker build . --tag transcription:latest
 
 W ten sposób zostanie zbudowany obraz `transcription:latest`. Teraz możemy go wykorzystać:
 ```
-$ docker run -v "$(pwd):/root/experiment" -it transcription:latest
+$ docker run -v "$(pwd):/root/experiment" -p 6006:6006 -it transcription:latest
 ```
 
 W ten sposób powinniśmy znaleźć się wewnątrz kontenera z skonfigurowanym środowiskiem i pobranym checkpointem. Katalog
 w którym się znajdujemy powinien być zamontowany w obrazie jako `~/experiment`.
+
+## Dataset
+Pliki midi zaczerpnięte z http://www.piano-midi.de/midi_files.htm stworzone przez Bernda Kruegera, udostępniane na licencji CC BY-SA 3.0. 
+
+Do przygotowania datasetu z załączonych plików `midi` należy skorzystać ze skryptu `prepare_dataset`. Pomoc i opis argumentów można uzyskać z pomocą argumentu `-h`.
+
+Przykładowe wywołanie:
+```
+python prepare_dataset.py -n 5
+```
+
+Wygeneruje dataset z pierwszych 5 plików midi w folderze `./dataset/midi`.
+
+Następnie należy przygotować dataset do działania z siecią:
+```
+python /opt/conda/envs/magenta/lib/python3.7/site-packages/magenta/models/onsets_frames_transcription/onsets_frames_transcription_create_tfrecords.py --csv="./dataset/manifest.csv" --output_directory="./dataset/processed" --wav_dir="./dataset/wav" --midi_dir="./dataset/midi" --expected_splits="test"
+```
+
+Niestety, w tej wersji jest błąd przez co alias `onsets_frames_transcription_create_tfrecords` nie działa i trzeba się ratować pełną ścieżką.
+
+Konwersję i testy możemy przeprowadzić komendą:
+```
+onsets_frames_transcription_infer --model_dir="${MODEL_DIR}" --output_dir="./eval/" --examples_path=./dataset/processed/test.tfrecord* --hparams="use_cudnn=false" --preprocess_examples=True
+```
+
+Parametr `--hparams="use_cudnn=false"` można pominąć jeżeli dysponujemy GPU z CUDA.
\ No newline at end of file
diff --git a/dataset/midi/chp_op18.mid b/dataset/midi/chp_op18.mid
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diff --git a/dataset/midi/mz_330_3.mid b/dataset/midi/mz_330_3.mid
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diff --git a/dataset/midi/ty_april.mid b/dataset/midi/ty_april.mid
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diff --git a/dataset/midi/ty_august.mid b/dataset/midi/ty_august.mid
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diff --git a/dataset/midi/ty_februar.mid b/dataset/midi/ty_februar.mid
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diff --git a/dataset/midi/ty_januar.mid b/dataset/midi/ty_januar.mid
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diff --git a/dataset/midi/ty_juli.mid b/dataset/midi/ty_juli.mid
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diff --git a/dataset/midi/ty_juni.mid b/dataset/midi/ty_juni.mid
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diff --git a/dataset/midi/ty_maerz.mid b/dataset/midi/ty_maerz.mid
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diff --git a/dataset/midi/ty_mai.mid b/dataset/midi/ty_mai.mid
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diff --git a/dataset/midi/ty_november.mid b/dataset/midi/ty_november.mid
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diff --git a/dataset/midi/ty_oktober.mid b/dataset/midi/ty_oktober.mid
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diff --git a/dataset/midi/ty_september.mid b/dataset/midi/ty_september.mid
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diff --git a/prepare_dataset.py b/prepare_dataset.py
new file mode 100644
index 0000000..371ed01
--- /dev/null
+++ b/prepare_dataset.py
@@ -0,0 +1,44 @@
+from glob import glob
+from argparse import ArgumentParser
+from os import system, path
+import csv
+
+
+parser = ArgumentParser(description="Prepare dataset from midi files for later use in onsets and frames.")
+parser.add_argument('--dry', '-d', dest='dry', action='store_true', help="Dry run, print commands instead of executing them")
+parser.add_argument('--no-convert', '-m', dest='no_convert', action='store_true', help="Only create manifest.")
+parser.add_argument('--soundfont', '-f', default='/usr/share/sounds/sf2/FluidR3_GM.sf2', help="Path to soundfont.")
+parser.add_argument('-n', type=int, help="Max midi files to process")
+
+args = parser.parse_args()
+
+execute = print if args.dry else system
+
+processed = 0
+if not args.no_convert:
+    for midi in glob("dataset/midi/*.mid"):
+        wav = midi.replace('.mid', '.wav').replace('/midi/', '/wav/')
+
+        processed = processed + 1
+        if 'n' in args and processed > args.n:
+            break
+
+        if path.isfile(wav):
+            continue
+
+        print(f"Converting {midi} to {wav}")
+        execute(f"fluidsynth -nli -r 48000 -T wav -F {wav} {args.soundfont} {midi} > /dev/null")
+
+
+manifest = []
+for wav in glob("dataset/wav/*.wav"):
+    midi = wav.replace('.wav', '.mid').replace('/wav/', '/midi/')
+
+    if path.isfile(midi):
+        manifest.append((path.basename(wav), path.basename(midi), 'test'))
+
+
+with open('dataset/manifest.csv', 'w') as manifest_file:
+    writer = csv.writer(manifest_file)
+    writer.writerow(('audio_filename', 'midi_filename', 'split'))
+    writer.writerows(manifest)
\ No newline at end of file