GitHub - collinswakholi/Image-Analysis-Beef-Yield-Estimation: Goal of this project was to predict beef carcass 22 yield parameters using image analysis. The code (written in MATLAB, Python) for image processing, feature extraction and multivariate modelling is found in this repository

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Goal of this project was to predict beef carcass 22 yield parameters using image analysis. The code (written in MATLAB, Python) for image processing, feature extraction and multivariate modelling is found in this repository

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Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
carcass_keypoint_detection		carcass_keypoint_detection
carcass_outline_detection		carcass_outline_detection
carcass_spine_detection		carcass_spine_detection
deep_learning_model		deep_learning_model
Center_max_cluster.m		Center_max_cluster.m
Extract_Features_from_Images.m		Extract_Features_from_Images.m
Extract_Features_from_Images_new.m		Extract_Features_from_Images_new.m
II.mat		II.mat
II2.mat		II2.mat
PLS_DA_SIMPLS.m		PLS_DA_SIMPLS.m
Range_normalize.m		Range_normalize.m
Readme.txt		Readme.txt
RefData_2019.xlsx		RefData_2019.xlsx
System_video.mp4		System_video.mp4
actual_pred_stats.m		actual_pred_stats.m
apply_msk.m		apply_msk.m
autoscale.m		autoscale.m
bb_2.m		bb_2.m
cal_val_new.m		cal_val_new.m
center.m		center.m
checklist4_Im.m		checklist4_Im.m
chooseFeat2.m		chooseFeat2.m
clean_masks.m		clean_masks.m
close_ends.m		close_ends.m
colsvm.m		colsvm.m
createMask_carcass.m		createMask_carcass.m
createMask_final.m		createMask_final.m
create_interaction_variables.m		create_interaction_variables.m
deep_predict.m		deep_predict.m
delete_manual.m		delete_manual.m
edge_msk.m		edge_msk.m
evaluate_keypoint_detection.m		evaluate_keypoint_detection.m
extract_name.m		extract_name.m
find_checkers.m		find_checkers.m
find_images_mask.m		find_images_mask.m
find_remove_checkers.m		find_remove_checkers.m
fit_mask.m		fit_mask.m
fitlm_model.m		fitlm_model.m
get_center_blob.m		get_center_blob.m
get_feat1.m		get_feat1.m
get_feat34.m		get_feat34.m
get_feat9.m		get_feat9.m
get_g_feat.m		get_g_feat.m
get_majority.m		get_majority.m
get_mask_improc.m		get_mask_improc.m
get_outliers.m		get_outliers.m
get_points.m		get_points.m
incl_external.m		incl_external.m
plot_points_lines.m		plot_points_lines.m
plot_polygons.m		plot_polygons.m
plot_residuals.m		plot_residuals.m
plot_results.m		plot_results.m
plsDA_VIP.m		plsDA_VIP.m
plsr_1.m		plsr_1.m
plsr_2.m		plsr_2.m
predVIP_REA_right_cold.fig		predVIP_REA_right_cold.fig
pred_REA_right_cold.fig		pred_REA_right_cold.fig
predict_regr.m		predict_regr.m
preprocess_data.m		preprocess_data.m
projections_qr.m		projections_qr.m
rank_featuresNCA.m		rank_featuresNCA.m
readImages.m		readImages.m
reg_coeeficients.fig		reg_coeeficients.fig
remove_bs.m		remove_bs.m

Repository files navigation

1. Run "my_mask.m" to extract masks from image datastore in out

2. Run "Extract_Features_from_Images_new.m" to extract features from images

3. Run "preprocess_data.m" to preprocess extracted features

4. Run "model_carcass2.m" to develop models for prediction carcass yield

see System_video.mp4