Computer_Vision/Chapter05/2D_and_3D_facial_keypoints.ipynb

!pip install -qU face-alignment torch_snippets
import face_alignment
from torch_snippets import read, show

     |████████████████████████████████| 61kB 3.0MB/s 
     |████████████████████████████████| 36.7MB 102kB/s 
     |████████████████████████████████| 102kB 9.2MB/s 
[?25h  Building wheel for contextvars (setup.py) ... [?25l[?25hdone

!wget https://www.dropbox.com/s/2s7xjto7rb6q7dc/Hema.JPG

--2020-10-09 08:02:03--  https://www.dropbox.com/s/2s7xjto7rb6q7dc/Hema.JPG
Resolving www.dropbox.com (www.dropbox.com)... 162.125.82.1, 2620:100:6032:1::a27d:5201
Connecting to www.dropbox.com (www.dropbox.com)|162.125.82.1|:443... connected.
HTTP request sent, awaiting response... 301 Moved Permanently
Location: /s/raw/2s7xjto7rb6q7dc/Hema.JPG [following]
--2020-10-09 08:02:03--  https://www.dropbox.com/s/raw/2s7xjto7rb6q7dc/Hema.JPG
Reusing existing connection to www.dropbox.com:443.
HTTP request sent, awaiting response... 302 Found
Location: https://uca0ee1ba76a0f56bcee98526bc1.dl.dropboxusercontent.com/cd/0/inline/BA7fn6ZPDWTae24PrMX4XwIJ4lbJZ18gdShIGu-rk1drszqsCZvrQRPHHwK8v9h_-JIpKYEE_ux3KvkpP122xv_FA03pu12Q-HF4TqQh8RV1GRpPpC1AAXn1K67aiWHyCtw/file# [following]
--2020-10-09 08:02:04--  https://uca0ee1ba76a0f56bcee98526bc1.dl.dropboxusercontent.com/cd/0/inline/BA7fn6ZPDWTae24PrMX4XwIJ4lbJZ18gdShIGu-rk1drszqsCZvrQRPHHwK8v9h_-JIpKYEE_ux3KvkpP122xv_FA03pu12Q-HF4TqQh8RV1GRpPpC1AAXn1K67aiWHyCtw/file
Resolving uca0ee1ba76a0f56bcee98526bc1.dl.dropboxusercontent.com (uca0ee1ba76a0f56bcee98526bc1.dl.dropboxusercontent.com)... 162.125.82.15, 2620:100:6032:15::a27d:520f
Connecting to uca0ee1ba76a0f56bcee98526bc1.dl.dropboxusercontent.com (uca0ee1ba76a0f56bcee98526bc1.dl.dropboxusercontent.com)|162.125.82.15|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 12860 (13K) [image/jpeg]
Saving to: ‘Hema.JPG’

Hema.JPG            100%[===================>]  12.56K  --.-KB/s    in 0s      

2020-10-09 08:02:04 (279 MB/s) - ‘Hema.JPG’ saved [12860/12860]

fa = face_alignment.FaceAlignment(face_alignment.LandmarksType._2D, flip_input=False, device='cpu')

Downloading: "https://www.adrianbulat.com/downloads/python-fan/s3fd-619a316812.pth" to /root/.cache/torch/hub/checkpoints/s3fd-619a316812.pth

HBox(children=(FloatProgress(value=0.0, max=89843225.0), HTML(value='')))

Downloading: "https://www.adrianbulat.com/downloads/python-fan/2DFAN4-11f355bf06.pth.tar" to /root/.cache/torch/hub/checkpoints/2DFAN4-11f355bf06.pth.tar

HBox(children=(FloatProgress(value=0.0, max=95641761.0), HTML(value='')))

input = read('Hema.JPG', 1)
preds = fa.get_landmarks(input)[0]
print(preds.shape)

(68, 3)

import matplotlib.pyplot as plt
%matplotlib inline
fig,ax = plt.subplots(figsize=(5,5))
show(read('Hema.JPG',1), ax=ax)
ax.scatter(preds[:,0], preds[:,1], marker='+', c='r')
plt.show()

fa = face_alignment.FaceAlignment(face_alignment.LandmarksType._3D, flip_input=False, device='cpu')
input = read('Hema.JPG', 1)
preds = fa.get_landmarks(input)[0]
import pandas as pd
df = pd.DataFrame(preds)
df.columns = ['x','y','z']
import plotly.express as px
fig = px.scatter_3d(df, x = 'x', y = 'y', z = 'z')
fig.show()