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Calculate distances for a pair of instances in the same frame or the same instance across frames

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Calculate distances for a pair of instances in the same frame or the same instance across frames#

import pandas as pd
import numpy as np
from google.colab import data_table

!pip install gradio

import gradio as gr

data_table.enable_dataframe_formatter()

CSV_FILE = '/content/mask_rcnn_tracking_results_with_segmenation.csv'

df = pd.read_csv(CSV_FILE)

df.head()

Calculate the distance of a pair of instances in a given frame#

def paired_distance(frame_number,
                    this_instance='Female_98',
                    other_instance='Male_109'):
    df_dis = df[df["frame_number"]==frame_number][['cx','cy','instance_name']]
    df_this = df_dis[df_dis.instance_name == this_instance]
    df_other = df_dis[df_dis.instance_name == other_instance]
    try:
      dist = np.linalg.norm(df_this[['cx','cy']].values-df_other[['cx','cy']].values)
    except:
      dist = None


    return dist

paired_distance(0,'Female_98','Male_109')

instance_names = list(df.instance_name.unique())

iface = gr.Interface(paired_distance,
                     [
                         gr.inputs.Number(),
                         gr.inputs.Dropdown(instance_names),
                         gr.inputs.Dropdown(instance_names),

                     ],
                     [
                         gr.outputs.Label(label="Paired Distance"),
                     ]
                     )
iface.launch()

Calculate the distance of the instance from the previous frame to the current frame#

def instance_distance_between_frame(frame_number,
                                    instance_name='Female_86'):
    if frame_number < 1:
      return 0
    previous_frame_number = frame_number - 1
    df_dis = df[df["frame_number"]==frame_number][['cx','cy','instance_name']]
    df_dis_prev = df[df["frame_number"]==previous_frame_number][['cx','cy','instance_name']]
    df_dis = df_dis[df_dis.instance_name == instance_name]
    df_dis_prev = df_dis_prev[df_dis_prev.instance_name == instance_name]

    try:
      dist = np.linalg.norm(df_dis[['cx','cy']].values-df_dis_prev[['cx','cy']].values)
    except:
      dist = None
    
    return dist
    

df['dist_from_previous_frame_female_86'] = df.frame_number.apply(instance_distance_between_frame,instance_name='Female_86')

df['dist_from_previous_frame_female_86'].describe()

The total distance traveled for instance female_86 in in pixels#

df['dist_from_previous_frame_female_86'].sum()

df['dist_from_previous_frame_male_109']= df.frame_number.apply(instance_distance_between_frame, instance_name='Male_109')

df['dist_from_previous_frame_male_109'].sum()

df['dist_from_previous_frame_female_98']= df.frame_number.apply(instance_distance_between_frame, instance_name='Female_98')

df['dist_from_previous_frame_female_98'].sum()

import plotly.express as px
import plotly.graph_objects as go

fig = px.line(x=df.frame_number, y=df.dist_from_previous_frame_female_86, labels={'x':'frame_number', 'y':'dist from previous frame female_86'})
fig.show()

Distance between two instances e.g. female_98 and male_109 in pixels#

df['dist_frog__female_98_male_109'] = df.frame_number.apply(paired_distance)

fig = px.line(x=df.frame_number, y=df.dist_frog__female_98_male_109, labels={'x':'frame_number', 'y':'distance between frog male in tank 2 to frog female in tank 2'})
fig.show()
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