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SeptAlfauzan
commited on
Commit
•
713f67e
1
Parent(s):
22cbc5d
add: model from training with hyper parameter epoch=120, batch=32 for SCB dataset and my own custom dataset
Browse files- app.py +10 -4
- models/OWN-DATASET-640-e120-b32-best.pt +3 -0
- models/SCB-640-e120-b32-best.pt +3 -0
- stream.py +55 -0
app.py
CHANGED
@@ -1,4 +1,5 @@
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import gradio as gr
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import torch
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from ultralyticsplus import YOLO, render_result
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@@ -11,23 +12,28 @@ def launch(
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):
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try:
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model_path = "./models/student-behaviour-best.pt"
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model = YOLO(
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results = model.predict(
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image, conf=conf_threshold, iou=iou_threshold, imgsz=image_size
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)
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box = results[0].boxes
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print(box)
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render = render_result(model=model, image=image, result=results[0])
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return render
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except Exception as e:
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print(e)
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return "./download.jpeg"
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inputs = [
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gr.Image(type="filepath", label="Input Image"),
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gr.Slider(minimum=
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gr.Slider(
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minimum=0.0, maximum=1.0, value=0.4, step=0.1, label="Confidence Threshold"
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),
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import gradio as gr
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from PIL import Image
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import torch
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from ultralyticsplus import YOLO, render_result
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):
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try:
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model_path = "./models/student-behaviour-best.pt"
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model = YOLO(
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"./student-behaviour-test-deploy/models/OWN-DATASET-640-e120-b32-best.pt"
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)
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# pil_image = Image.fromarray(image)
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results = model.predict(
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image, conf=conf_threshold, iou=iou_threshold, imgsz=image_size
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)
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box = results[0].boxes
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# print(box)
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render = render_result(model=model, image=image, result=results[0])
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return render
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except Exception as e:
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print("error", e)
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return "./download.jpeg"
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inputs = [
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gr.Image(type="filepath", label="Input Image"),
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gr.Slider(minimum=256, maximum=1280, value=640, step=32, label="Image Size"),
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gr.Slider(
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minimum=0.0, maximum=1.0, value=0.4, step=0.1, label="Confidence Threshold"
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),
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models/OWN-DATASET-640-e120-b32-best.pt
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:5b433715b811e36de8e8e83e89bc84e808a66b68055eb2e4925a9dd5c95f78da
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size 6260441
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models/SCB-640-e120-b32-best.pt
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:c3297bff6efde17917d641eacf69137eee010ba34c17e837eff8721a3acc1ee0
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size 6260697
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stream.py
ADDED
@@ -0,0 +1,55 @@
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import gradio as gr
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from pydub import AudioSegment
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from time import sleep
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with gr.Blocks() as demo:
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input_audio = gr.Audio(label="Input Audio", type="filepath", format="mp3")
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with gr.Row():
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with gr.Column():
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stream_as_file_btn = gr.Button("Stream as File")
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format = gr.Radio(["wav", "mp3"], value="wav", label="Format")
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stream_as_file_output = gr.Audio(streaming=True)
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def stream_file(audio_file, format):
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audio = AudioSegment.from_file(audio_file)
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i = 0
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chunk_size = 1000
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while chunk_size * i < len(audio):
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chunk = audio[chunk_size * i : chunk_size * (i + 1)]
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i += 1
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if chunk:
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file = f"/tmp/{i}.{format}"
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chunk.export(file, format=format)
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yield file
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sleep(0.5)
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stream_as_file_btn.click(
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stream_file, [input_audio, format], stream_as_file_output
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)
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gr.Examples(
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[["audio/cantina.wav", "wav"], ["audio/cantina.wav", "mp3"]],
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[input_audio, format],
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fn=stream_file,
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outputs=stream_as_file_output,
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)
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with gr.Column():
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stream_as_bytes_btn = gr.Button("Stream as Bytes")
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stream_as_bytes_output = gr.Audio(format="bytes", streaming=True)
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def stream_bytes(audio_file):
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chunk_size = 20_000
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with open(audio_file, "rb") as f:
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while True:
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chunk = f.read(chunk_size)
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if chunk:
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yield chunk
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sleep(1)
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else:
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break
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stream_as_bytes_btn.click(stream_bytes, input_audio, stream_as_bytes_output)
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if __name__ == "__main__":
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demo.queue().launch()
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