In [1]:

from PIL import Image
from fall_prediction import Fall_prediction
import matplotlib.pyplot as plt

For Two Images¶

In [2]:

img1 = Image.open("Images/fall_img_1.png")
img2 = Image.open("Images/fall_img_2.png")

In [3]:

fig = plt.figure(figsize=(10, 7))
fig.add_subplot(1, 2, 1)
plt.imshow(img1)
plt.title("Image at time t")
plt.axis("off")

fig.add_subplot(1, 2, 2)
plt.imshow(img2)
plt.title("Image at time t+1 ")
plt.axis("off")

plt.show()

In [4]:

response = Fall_prediction(img1,img2)
if response:
    print("There is", response['category'])
    print("Confidence :", response['confidence'])
    print("Angle : ", response['angle'])
    print("Keypoint_corr :", response['keypoint_corr'])
else:
     print("There is no fall detetcion...")

There is no fall detetcion...

For Three Images¶

In [5]:

img1 = Image.open("Images/fall_img_1.png")
img2 = Image.open("Images/fall_img_2.png")
img3 = Image.open("Images/fall_img_3.png")

In [6]:

fig = plt.figure(figsize=(12,12))
fig.add_subplot(1, 3, 1)
plt.imshow(img1)
plt.title("image at time t")
plt.axis("off")

fig.add_subplot(1, 3, 2)
plt.imshow(img2)
plt.title("image at time t+1")
plt.axis("off")

fig.add_subplot(1, 3, 3)
plt.imshow(img3)
plt.title("image at time t+2")
plt.axis("off")

plt.show()

In [7]:

response = Fall_prediction(img1,img2,img3)
if response:
    print("There is", response['category'])
    print("Confidence :", response['confidence'])
    print("Angle : ", response['angle'])
    print("Keypoint_corr :", response['keypoint_corr'])
else:
     print("There is no fall detetcion...")

There is FALL
Confidence : 0.8991963234324727
Angle :  69.17818735314414
Keypoint_corr : {'left shoulder': [104.0, 113.0], 'left hip': [135.0, 128.0], 'right shoulder': [95.0, 112.0], 'right hip': [138.0, 127.0]}

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