Spaces:
Sleeping
Sleeping
File size: 1,803 Bytes
52dce0a 915d664 92badd3 7008c4a 52dce0a 83fe5b0 52dce0a 55a5bfa 52dce0a 55a5bfa 3b197de 52dce0a 55a5bfa 9d3accc e01d5f6 9d3accc f03708e d152f7f 1d5816e 86680ae 0a1d185 d152f7f 99ab932 d152f7f e01d5f6 d152f7f 7c72540 d152f7f 1d5816e 52dce0a |
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 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 |
from pathlib import Path
from typing import List, Dict, Tuple
import pandas as pd
import seaborn as sns
import shinyswatch
import run
import os
os.environ['MPLCONFIGDIR'] = "/code/configs"
import matplotlib.pyplot as plt
from shiny import App, Inputs, Outputs, Session, reactive, render, req, ui
from transformers import SamModel, SamConfig, SamProcessor
import torch
sns.set_theme()
www_dir = Path(__file__).parent.resolve() / "www"
app_ui = ui.page_fillable(
shinyswatch.theme.minty(),
ui.layout_sidebar(
ui.sidebar(
ui.input_file("image_input", "Upload image: ", multiple=True),
),
ui.output_image("image"),
ui.output_plot("plot_output", fill=True),
),
)
def server(input: Inputs, output: Outputs, session: Session):
@output
@render.image
def image():
if input.image_input():
src = input.image_input()[0]['datapath']
img = {"src": src, "width": "500px"}
return img
return None
@output
@render.plot
def plot_output():
if input.image_input():
src = input.image_input()[0]['datapath']
prob, prediction = run.pred(src)
fig, axes = plt.subplots(1, 2, figsize=(60, 30))
im = axes[0].imshow(prob, cmap='viridis')
axes[0].set_title("Probability Map")
cbar = fig.colorbar(im, ax=axes[0])
axes[1].imshow(prediction, cmap='gray')
axes[1].set_title("Prediction")
for ax in axes:
ax.set_xticks([])
ax.set_yticks([])
ax.set_xticklabels([])
ax.set_yticklabels([])
return fig
return None
app = App(
app_ui,
server,
static_assets=str(www_dir),
)
|