Spaces:
Sleeping
Sleeping
Added logging widget and logic
Browse files- demo/src/gui.py +70 -53
- demo/src/inference.py +2 -1
- demo/src/logger.py +30 -0
demo/src/gui.py
CHANGED
@@ -3,11 +3,16 @@ import os
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import gradio as gr
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from .inference import run_model
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from .utils import load_ct_to_numpy
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from .utils import load_pred_volume_to_numpy
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from .utils import nifti_to_glb
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class WebUI:
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def __init__(
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self,
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@@ -102,67 +107,79 @@ class WebUI:
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#upload {
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height: 120px;
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}
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"""
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with gr.Blocks(css=css) as demo:
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with gr.Row():
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run_btn = gr.Button("Run analysis").style(
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full_width=False, size="lg"
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)
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run_btn.click(
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fn=lambda x: self.process(x),
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inputs=file_output,
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outputs=self.volume_renderer,
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)
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with gr.Row():
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gr.Examples(
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examples=[
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os.path.join(self.cwd, "test_thorax_CT.nii.gz"),
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],
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inputs=file_output,
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outputs=file_output,
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fn=self.upload_file,
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cache_examples=True,
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)
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with gr.Row():
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with gr.Box():
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with gr.Column():
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# create dummy image to be replaced by loaded images
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t = gr.AnnotatedImage(
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visible=True, elem_id="model-2d"
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).style(
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color_map={self.class_name: "#ffae00"},
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height=512,
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width=512,
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)
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)
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# sharing app publicly -> share=True:
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# https://gradio.app/sharing-your-app/
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import gradio as gr
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from .inference import run_model
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from .logger import setup_logger, read_logs
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from .utils import load_ct_to_numpy
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from .utils import load_pred_volume_to_numpy
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from .utils import nifti_to_glb
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# setup logging
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LOGGER = setup_logger()
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class WebUI:
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def __init__(
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self,
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#upload {
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height: 120px;
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}
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.logs {
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width: 120px;
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margin: auto;
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}
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"""
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with gr.Blocks(css=css) as demo:
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with gr.Row():
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with gr.Column():
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with gr.Row():
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file_output = gr.File(file_count="single", elem_id="upload")
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file_output.upload(self.upload_file, file_output, file_output)
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model_selector = gr.Dropdown(
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list(self.class_names.keys()),
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label="Task",
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info="Which task to perform",
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multiselect=False,
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size="sm",
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)
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model_selector.input(
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fn=lambda x: self.set_class_name(x),
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inputs=model_selector,
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outputs=None,
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)
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run_btn = gr.Button("Run analysis").style(
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full_width=False, size="lg"
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)
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run_btn.click(
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fn=lambda x: self.process(x),
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inputs=file_output,
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outputs=self.volume_renderer,
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)
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with gr.Row():
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gr.Examples(
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examples=[
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os.path.join(self.cwd, "test_thorax_CT.nii.gz"),
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],
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inputs=file_output,
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outputs=file_output,
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fn=self.upload_file,
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cache_examples=True,
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)
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with gr.Row():
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with gr.Box():
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with gr.Column():
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# create dummy image to be replaced by loaded images
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t = gr.AnnotatedImage(
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visible=True, elem_id="model-2d"
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).style(
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color_map={self.class_name: "#ffae00"},
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height=512,
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width=512,
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)
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self.slider.input(
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self.get_img_pred_pair,
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self.slider,
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t,
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)
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self.slider.render()
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with gr.Box():
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self.volume_renderer.render()
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with gr.Column(visible=True, style="logs", scale=0.2) as sidebar_left:
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gr.Markdown("SideBar Right")
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logs = gr.Textbox(label="Logs", info="Verbose from inference will be displayed below.", max_lines=16, autoscroll=True, elem_id="logs")
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demo.load(read_logs, None, logs, every=1)
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# sharing app publicly -> share=True:
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# https://gradio.app/sharing-your-app/
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demo/src/inference.py
CHANGED
@@ -4,6 +4,8 @@ import os
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import shutil
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import traceback
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def run_model(
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input_path: str,
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task: str = "CT_Airways",
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name: str = "Airways",
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):
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logging.basicConfig()
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logging.getLogger().setLevel(logging.WARNING)
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if verbose == "debug":
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import shutil
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import traceback
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from .logger import get_logger
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def run_model(
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input_path: str,
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task: str = "CT_Airways",
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name: str = "Airways",
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):
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logging.getLogger().setLevel(logging.WARNING)
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if verbose == "debug":
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demo/src/logger.py
ADDED
@@ -0,0 +1,30 @@
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import logging
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import sys
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def get_logger():
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logging.getLogger(__name__)
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def setup_logger():
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# clear log
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file_to_delete = open("log.txt", "w")
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file_to_delete.close()
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file_handler = logging.FileHandler(filename="log.txt")
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stdout_handler = logging.StreamHandler(stream=sys.stdout)
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handlers = [file_handler, stdout_handler]
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logging.basicConfig(
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level=logging.INFO,
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format='[%(asctime)s] {%(filename)s:%(lineno)d} %(levelname)s - %(message)s',
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handlers=handlers,
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)
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return get_logger()
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def read_logs():
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sys.stdout.flush()
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with open("log.txt", "r") as f:
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return f.read()
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