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import cv2 |
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import os |
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import plotly.express as px |
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import numpy as np |
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import pandas as pd |
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from plotly.subplots import make_subplots |
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import plotly.io as pio |
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pio.kaleido.scope.mathjax = None |
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def distribute_glacier(list_of_samples): |
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list_of_glaciers = {} |
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for glacier in [ 'COL', 'Mapple', 'Crane', 'Jorum','DBE','SI', 'JAC']: |
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list_of_glaciers[glacier] = [sample for sample in list_of_samples if glacier in sample] |
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return list_of_glaciers |
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if __name__ == '__main__': |
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generate_data = True |
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if generate_data: |
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train_dir = '/home/ho11laqe/PycharmProjects/data_raw/zones/train' |
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test_dir = '/home/ho11laqe/PycharmProjects/data_raw/zones/test' |
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list_of_train_samples = [] |
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for sample in os.listdir(train_dir): |
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list_of_train_samples.append(os.path.join(train_dir, sample)) |
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list_of_test_samples = [] |
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for sample in os.listdir(test_dir): |
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list_of_test_samples.append(os.path.join(test_dir, sample)) |
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list_of_samples = list_of_train_samples + list_of_test_samples |
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list_of_glacier = distribute_glacier(list_of_samples) |
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fig = make_subplots(rows=len(list_of_glacier.keys()), cols=1) |
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nan = [] |
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rock = [] |
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ice = [] |
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ocean = [] |
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date = [] |
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glacier_name = [] |
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for i, glacier in enumerate(list_of_glacier.keys()): |
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for sample in list_of_glacier[glacier]: |
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print(sample) |
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seg_mask = cv2.imread(sample, cv2.IMREAD_GRAYSCALE) |
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all_pixel = seg_mask.shape[0] * seg_mask.shape[1] |
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nan.append(np.count_nonzero(seg_mask == 0) / all_pixel * 100) |
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rock.append(np.count_nonzero(seg_mask == 64) / all_pixel * 100) |
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ice.append(np.count_nonzero(seg_mask == 127) / all_pixel * 100) |
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ocean.append(np.count_nonzero(seg_mask == 254) / all_pixel * 100) |
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sample_split = sample.split('_') |
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date.append(sample_split[-6]) |
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glacier_name.append(glacier) |
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df = pd.DataFrame(dict(Shadow=nan, Rock=rock, Glacier=ice, Ocean=ocean, date=date, glacier_name=glacier_name)) |
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df.to_csv('output/area.csv') |
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else: |
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df = pd.read_csv('output/area.csv') |
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df = df.drop_duplicates(subset=['date', 'glacier_name']) |
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area_plot = px.area(df, |
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x="date", |
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y=["Rock", "Shadow", "Glacier", "Ocean"], |
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color_discrete_map={"Shadow": 'black', "Ocean": 'blue', "Glacier": "aliceblue", "Rock": "gray"}, |
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template="plotly_white", |
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height=700, |
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width =600, |
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facet_row='glacier_name', |
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category_orders={'glacier': [ 'COL', 'Mapple', 'Crane', 'Jorum','DBE','SI', 'JAC']} |
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) |
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area_plot.update_yaxes(type='linear', range=[0, 100], ticksuffix='%', title='area', side='right') |
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area_plot.for_each_annotation(lambda a: a.update(text=a.text.split("=")[1], textangle=0, x=0, xanchor='right')) |
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area_plot.update_layout(legend=dict(title='Area:', |
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orientation="h", |
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yanchor="bottom", |
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y=1.02, |
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xanchor="right", |
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x=1, |
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font=dict(size=12)), |
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margin=dict(l=70, r=0, t=0, b=0) |
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) |
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area_plot.for_each_yaxis(lambda a: a.update(title='')) |
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area_plot.update_xaxes(title=' ',tickfont=dict(size=12)) |
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area_plot.update_layout(font=dict(family="Times New Roma", size=10, )) |
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area_plot.update_annotations(font=dict(size=12)) |
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area_plot.write_image("output/area.pdf", format='pdf') |
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