body-matrix 0.0.4

Package to Calculate Human Body Measurements

Human Body Measurement via Video and Image

Install Package

$ pip install body-matrix

Package Usage

Load Models, Video and Image Frames Load Segmentation Model to CPU

from body_matrix import load
segmentation_model, segmentation_transforms = load.segmentation_model("cpu")

Load Segmentation Model to GPU

from body_matrix import load
segmentation_model, segmentation_transforms = load.segmentation_model("cuda")

Load Keypoints Model to CPU

from body_matrix import load
keypoints_model, keypoints_transforms = load.segmentation_model("cpu")

Load Keypoints Model to GPU

from body_matrix import load
keypoints_model, keypoints_transforms = load.segmentation_model("cuda")

Load Video

from body_matrix import load
video, frames_counts, fps, sample_frame = load.video("/Desktop/dt.mov", 90, 1)
print(frames_counts)

Load Image

from body_matrix import load
frames_path = load.image_frames("/Desktop/instagram")
print(frames_path)

Infer Detect_Main_Target

from body_matrix import infer
from body_matrix import load

keypoints_model, keypoints_transform = load.keypoints_model("cpu")
video, frame_counts, fps, sample_frame = load.video("04_01.mp4", -90, 1)

selected_box, keypoint = infer.detect_main_target(
    sample_frame, "cpu", 0.8, keypoints_model, keypoints_transform
)

Segment_Selected_Target

from body_matrix import infer
from body_matrix import load

segment_model, segment_transform = load.segment_model("cpu")
video, frame_counts, fps, sample_frame = load.video("04_01.mp4", -90, 1)

selected_box, keypoint = infer.detect_main_target(
    sample_frame, "cpu", 0.8, keypoints_model, keypoints_transform
)

mask, mask_image, bool_mask = infer.segment_selected_target(
    sample_frame, "cpu", selected_box, 0.99, segment_model, segment_transform
)

Filter Keypoints_Filter

from body_matrix import load
from body_matrix import infer
from body_matrix import process

video, frame_counts, fps, sample_frame = load.video(
    "sample02.mp4", 
    -90, 
    1
)

keypoints_model, keypoints_transform = load.keypoints_model("cpu")
boxes, keypoints = infer.detect_main_target(
    sample_frame, "cpu", 0.8, keypoints_model, keypoints_transform
)

selected_kps = process.keypoints_filter(
	['nose','left_shoulder','right_shoulder'], 
	keypoints
)

print(selected_kps[nose])

Human_Segmentation_Area

from body_matrix import load
from body_matrix import infer
from body_matrix import process

video, frame_counts, fps, sample_frame = load.video(
    "sample02.mp4", 
    -90, 
    1
)

keypoints_model, keypoints_transform = load.keypoints_model("cpu")
boxes, keypoints = infer.detect_main_target(
    sample_frame, "cpu", 0.8, keypoints_model, keypoints_transform
)

selected_kps = process.keypoints_filter(
	['nose','left_shoulder','right_shoulder'], 
	keypoints
)

segment_model, segment_transform = load.segment_model("cpu")
mask, mask_image, bool_mask = infer.segment_selected_target(
    sample_frame, "cpu", selected_box, 0.99, segment_model, segment_transform
)

segment_area = process.segmentation_area(
    sample_frame, 
    bool_mask
)

Find_Segmentation_Intersection Find_Segmentation_Contour - TO be DONE Filter_Segmentation_Intersection

Measure Get_Box_Center_Coordinate Two_Boxes_Distance Box_Distance_From_Vertical_Line Box_Distance_From_Horizontal_Line Box_Distance_From_Center Two_Points_Distance Find_Middle_Point Find_Border_Length - TO be DONE Find_Polygon_Area - TO be DONE

Visualize Draw_Keypoint_Markers Draw_Circle_Label Draw_Rectangle_Label Draw_Connecting_Line

Score Find_Nearest_Value Find_Largest_Value Find_Best_Score

Export Generate_Video_From_Images Generate_Seeking_Video_From_Images Generate_Instagram_Video_From_Images Generate_Youtube_Video_From_Images