This is a simple example.
from gluoncv import model_zoo, data, utils
from gluoncv.data.transforms.pose import detector_to_simple_pose,
heatmap_to_coord
detector = model_zoo.get_model('yolo3_mobilenet1.0_coco', pretrained=True,
root='./model')
pose_net = model_zoo.get_model('simple_pose_resnet18_v1b', pretrained=True,
root='./model')
detector.reset_class(["person"], reuse_weights=['person'])
url =
'https://raw.githubusercontent.com/dmlc/web-data/master/gluoncv/segmentation/mhpv1_examples/1.jpg'
filename = 'sample.jpg'
utils.download(url, filename)
x, img = data.transforms.presets.ssd.load_test(filename, short=512)
class_IDs, scores, bounding_boxs = detector(x)
pose_input, upscale_bbox = detector_to_simple_pose(img, class_IDs, scores,
bounding_boxs)
predicted_heatmap = pose_net(pose_input)
pred_coords, confidence = heatmap_to_coord(predicted_heatmap, upscale_bbox)
from PIL import Image, ImageDraw
pil_image = Image.fromarray(img)
draw = ImageDraw.Draw(pil_image)
keypoints = data.mscoco.keypoints.COCOKeyPoints.KEYPOINTS
for keypoint_id in range(len(keypoints)):
pred = pred_coords[:,keypoint_id,:]
for i in range(pred.shape[0]):
if (confidence[i,keypoint_id,:] > 0.2) == 1:
draw.text(pred[i,:].asnumpy(),text=keypoints[keypoint_id],
fill='red')
pil_image.show()
---
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Topic](https://discuss.mxnet.apache.org/t/how-to-find-which-part-of-body-the-keypoint-relates-to-in-pose-estimation/6468/4)
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