How to use the plantcv.rgb2gray_lab function in plantcv

To help you get started, we’ve selected a few plantcv examples, based on popular ways it is used in public projects.

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danforthcenter / plantcv / scripts / dev / gehan_brachy / vis-sv / vis_sv_z3500_L2_e82.py View on Github

# Threshold the blue image
  device, b_thresh = pcv.binary_threshold(b, 137, 255, 'light', device, args.debug)
  device, b_cnt = pcv.binary_threshold(b, 137, 255, 'light', device, args.debug)
  
  # Fill small objects
  #device, b_fill = pcv.fill(b_thresh, b_cnt, 10, device, args.debug)
  
  # Join the thresholded saturation and blue-yellow images
  device, bs = pcv.logical_and(s_mblur, b_cnt, device, args.debug)
  
  # Apply Mask (for vis images, mask_color=white)
  device, masked = pcv.apply_mask(img, bs, 'white', device, args.debug)
  
  # Convert RGB to LAB and extract the Green-Magenta and Blue-Yellow channels
  device, masked_a = pcv.rgb2gray_lab(masked, 'a', device, args.debug)
  device, masked_b = pcv.rgb2gray_lab(masked, 'b', device, args.debug)
  
  # Threshold the green-magenta and blue images
  device, maskeda_thresh = pcv.binary_threshold(masked_a, 127, 255, 'dark', device, args.debug)
  device, maskedb_thresh = pcv.binary_threshold(masked_b, 128, 255, 'light', device, args.debug)
  
  # Join the thresholded saturation and blue-yellow images (OR)
  device, ab = pcv.logical_or(maskeda_thresh, maskedb_thresh, device, args.debug)
  device, ab_cnt = pcv.logical_or(maskeda_thresh, maskedb_thresh, device, args.debug)
  
  # Fill small noise
  device, ab_fill1 = pcv.fill(ab, ab_cnt, 2, device, args.debug)
  
  # Dilate to join small objects with larger ones
  device, ab_cnt1=pcv.dilate(ab_fill1, 3, 2, device, args.debug)
  device, ab_cnt2=pcv.dilate(ab_fill1, 3, 2, device, args.debug)

danforthcenter / plantcv / scripts / dev / gehan_brachy / vis-nir-tv / vis_nir_tv_z2500_h2_e82_brachy_drought.py View on Github

device, b_fill = pcv.fill(b_thresh, b_cnt, 150, device, args.debug)
  
  # Join the thresholded saturation and blue-yellow images
  device, bs = pcv.logical_and(s_fill, b_fill, device, args.debug)
  
  # Apply Mask (for vis images, mask_color=white)
  device, masked = pcv.apply_mask(img, bs,'white', device, args.debug)
    
  # Mask pesky brass piece
  device, brass_mask1 = pcv.rgb2gray_hsv(brass_mask, 'v', device, args.debug)
  device, brass_thresh = pcv.binary_threshold(brass_mask1, 0, 255, 'light', device, args.debug)
  device, brass_inv=pcv.invert(brass_thresh, device, args.debug)
  device, brass_masked = pcv.apply_mask(masked, brass_inv, 'white', device, args.debug)
  
  # Further mask soil and car
  device, masked_a = pcv.rgb2gray_lab(brass_masked, 'a', device, args.debug)
  device, soil_car1 = pcv.binary_threshold(masked_a, 128, 255, 'dark', device, args.debug)
  device, soil_car2 = pcv.binary_threshold(masked_a, 128, 255, 'light', device, args.debug)
  device, soil_car=pcv.logical_or(soil_car1, soil_car2,device, args.debug)
  device, soil_masked = pcv.apply_mask(brass_masked, soil_car, 'white', device, args.debug)
  
  # Convert RGB to LAB and extract the Green-Magenta and Blue-Yellow channels
  device, soil_a = pcv.rgb2gray_lab(soil_masked, 'a', device, args.debug)
  device, soil_b = pcv.rgb2gray_lab(soil_masked, 'b', device, args.debug)
  
  # Threshold the green-magenta and blue images
  device, soila_thresh = pcv.binary_threshold(soil_a, 124, 255, 'dark', device, args.debug)
  device, soilb_thresh = pcv.binary_threshold(soil_b, 148, 255, 'light', device, args.debug)

  # Join the thresholded saturation and blue-yellow images (OR)
  device, soil_ab = pcv.logical_or(soila_thresh, soilb_thresh, device, args.debug)
  device, soil_ab_cnt = pcv.logical_or(soila_thresh, soilb_thresh, device, args.debug)

danforthcenter / plantcv / scripts / dev / gehan_brachy / new-for_cesar / vis_sv_z2500_L2_e82.py View on Github

# Threshold the blue image
  device, b_thresh = pcv.binary_threshold(b, 137, 255, 'light', device, args.debug)
  device, b_cnt = pcv.binary_threshold(b, 137, 255, 'light', device, args.debug)
  
  # Fill small objects
  #device, b_fill = pcv.fill(b_thresh, b_cnt, 10, device, args.debug)
  
  # Join the thresholded saturation and blue-yellow images
  device, bs = pcv.logical_and(s_mblur, b_cnt, device, args.debug)
  
  # Apply Mask (for vis images, mask_color=white)
  device, masked = pcv.apply_mask(img, bs, 'white', device, args.debug)
  
  # Convert RGB to LAB and extract the Green-Magenta and Blue-Yellow channels
  device, masked_a = pcv.rgb2gray_lab(masked, 'a', device, args.debug)
  device, masked_b = pcv.rgb2gray_lab(masked, 'b', device, args.debug)
  
  # Threshold the green-magenta and blue images
  device, maskeda_thresh = pcv.binary_threshold(masked_a, 127, 255, 'dark', device, args.debug)
  device, maskedb_thresh = pcv.binary_threshold(masked_b, 128, 255, 'light', device, args.debug)
  
  # Join the thresholded saturation and blue-yellow images (OR)
  device, ab = pcv.logical_or(maskeda_thresh, maskedb_thresh, device, args.debug)
  device, ab_cnt = pcv.logical_or(maskeda_thresh, maskedb_thresh, device, args.debug)
  
   # Fill small noise
  device, ab_fill1 = pcv.fill(ab, ab_cnt, 2, device, args.debug)
  
  # Dilate to join small objects with larger ones
  device, ab_cnt1=pcv.dilate(ab_fill1, 3, 2, device, args.debug)
  device, ab_cnt2=pcv.dilate(ab_fill1, 3, 2, device, args.debug)

danforthcenter / plantcv / scripts / dev / gehan_brachy / vis-nir-sv / vis_nir_sv_z500_h2_e82_brachy_drought.py View on Github

# Threshold the blue image
  device, b_thresh = pcv.binary_threshold(b, 137, 255, 'light', device, args.debug)
  device, b_cnt = pcv.binary_threshold(b, 137, 255, 'light', device, args.debug)
  
  # Fill small objects
  #device, b_fill = pcv.fill(b_thresh, b_cnt, 10, device, args.debug)
  
  # Join the thresholded saturation and blue-yellow images
  device, bs = pcv.logical_and(s_mblur, b_cnt, device, args.debug)
  
  # Apply Mask (for vis images, mask_color=white)
  device, masked = pcv.apply_mask(img, bs, 'white', device, args.debug)
  
  # Convert RGB to LAB and extract the Green-Magenta and Blue-Yellow channels
  device, masked_a = pcv.rgb2gray_lab(masked, 'a', device, args.debug)
  device, masked_b = pcv.rgb2gray_lab(masked, 'b', device, args.debug)
  
  # Threshold the green-magenta and blue images
  device, maskeda_thresh = pcv.binary_threshold(masked_a, 127, 255, 'dark', device, args.debug)
  device, maskedb_thresh = pcv.binary_threshold(masked_b, 128, 255, 'light', device, args.debug)
  
  # Join the thresholded saturation and blue-yellow images (OR)
  device, ab = pcv.logical_or(maskeda_thresh, maskedb_thresh, device, args.debug)
  device, ab_cnt = pcv.logical_or(maskeda_thresh, maskedb_thresh, device, args.debug)
  
  # Fill small noise
  device, ab_fill1 = pcv.fill(ab, ab_cnt, 2, device, args.debug)
  
  # Dilate to join small objects with larger ones
  device, ab_cnt1=pcv.dilate(ab_fill1, 3, 2, device, args.debug)
  device, ab_cnt2=pcv.dilate(ab_fill1, 3, 2, device, args.debug)

danforthcenter / plantcv / scripts / dev / gehan_brachy / vis-sv / vis_sv_z500_frame0_L1_e82.py View on Github

device, ab = pcv.logical_or(maskeda_thresh, maskedb_thresh, device, args.debug)
  device, ab_cnt = pcv.logical_or(maskeda_thresh, maskedb_thresh, device, args.debug)
  
  # Fill small noise
  device, ab_fill1 = pcv.fill(ab, ab_cnt, 2, device, args.debug)
  
  # Dilate to join small objects with larger ones
  device, ab_cnt1=pcv.dilate(ab_fill1, 3, 2, device, args.debug)
  device, ab_cnt2=pcv.dilate(ab_fill1, 3, 2, device, args.debug)
  
  # Fill dilated image mask
  device, ab_cnt3=pcv.fill(ab_cnt2,ab_cnt1,150,device,args.debug)
  device, masked2 = pcv.apply_mask(masked, ab_cnt3, 'white', device, args.debug)
  
  # Convert RGB to LAB and extract the Green-Magenta and Blue-Yellow channels
  device, masked2_a = pcv.rgb2gray_lab(masked2, 'a', device, args.debug)
  device, masked2_b = pcv.rgb2gray_lab(masked2, 'b', device, args.debug)
  
  # Threshold the green-magenta and blue images
  device, masked2a_thresh = pcv.binary_threshold(masked2_a, 127, 255, 'dark', device, args.debug)
  device, masked2b_thresh = pcv.binary_threshold(masked2_b, 128, 255, 'light', device, args.debug)
  device, ab_fill = pcv.logical_or(masked2a_thresh, masked2b_thresh, device, args.debug)
  
  # Identify objects
  device, id_objects,obj_hierarchy = pcv.find_objects(masked2, ab_fill, device, args.debug)
  
  # Define ROI
  device, roi1, roi_hierarchy= pcv.define_roi(masked2,'rectangle', device, None, 'default', args.debug,True, 525, 0,-490,-150)
  
  # Decide which objects to keep
  device,roi_objects, hierarchy3, kept_mask, obj_area = pcv.roi_objects(img,'partial',roi1,roi_hierarchy,id_objects,obj_hierarchy,device, args.debug)

danforthcenter / plantcv / scripts / dev / vis_sv_z500_L1_e82.py View on Github

# Threshold the blue image
  device, b_thresh = pcv.binary_threshold(b, 137, 255, 'light', device, args.debug)
  device, b_cnt = pcv.binary_threshold(b, 137, 255, 'light', device, args.debug)
  
  # Fill small objects
  #device, b_fill = pcv.fill(b_thresh, b_cnt, 150, device, args.debug)
  
  # Join the thresholded saturation and blue-yellow images
  device, bs = pcv.logical_and(s_mblur, b_cnt, device, args.debug)
  
  # Apply Mask (for vis images, mask_color=white)
  device, masked = pcv.apply_mask(img, bs, 'white', device, args.debug)
  
  # Convert RGB to LAB and extract the Green-Magenta and Blue-Yellow channels
  device, masked_a = pcv.rgb2gray_lab(masked, 'a', device, args.debug)
  device, masked_b = pcv.rgb2gray_lab(masked, 'b', device, args.debug)
  
  # Threshold the green-magenta and blue images
  device, maskeda_thresh = pcv.binary_threshold(masked_a, 127, 255, 'dark', device, args.debug)
  device, maskedb_thresh = pcv.binary_threshold(masked_b, 128, 255, 'light', device, args.debug)
  
  # Join the thresholded saturation and blue-yellow images (OR)
  device, ab = pcv.logical_or(maskeda_thresh, maskedb_thresh, device, args.debug)
  device, ab_cnt = pcv.logical_or(maskeda_thresh, maskedb_thresh, device, args.debug)
  
  # Fill small objects
  device, ab_fill = pcv.fill(ab, ab_cnt, 2, device, args.debug)
  
  # Apply mask (for vis images, mask_color=white)
  device, masked2 = pcv.apply_mask(masked, ab_fill, 'white', device, args.debug)
  
  # Select area with black bars and find overlapping plant material

danforthcenter / plantcv / scripts / dev / gehan_brachy / new-for_cesar / vis_tv_z2500_L2_e82 copy.py View on Github

# Mask pesky brass piece
  device, brass_mask1 = pcv.rgb2gray_hsv(brass_mask, 'v', device, args.debug)
  device, brass_thresh = pcv.binary_threshold(brass_mask1, 0, 255, 'light', device, args.debug)
  device, brass_inv=pcv.invert(brass_thresh, device, args.debug)
  device, brass_masked = pcv.apply_mask(masked, brass_inv, 'white', device, args.debug)
  
  # Further mask soil and car
  device, masked_a = pcv.rgb2gray_lab(brass_masked, 'a', device, args.debug)
  device, soil_car1 = pcv.binary_threshold(masked_a, 128, 255, 'dark', device, args.debug)
  device, soil_car2 = pcv.binary_threshold(masked_a, 128, 255, 'light', device, args.debug)
  device, soil_car=pcv.logical_or(soil_car1, soil_car2,device, args.debug)
  device, soil_masked = pcv.apply_mask(brass_masked, soil_car, 'white', device, args.debug)
  
  # Convert RGB to LAB and extract the Green-Magenta and Blue-Yellow channels
  device, soil_a = pcv.rgb2gray_lab(soil_masked, 'a', device, args.debug)
  device, soil_b = pcv.rgb2gray_lab(soil_masked, 'b', device, args.debug)
  
  # Threshold the green-magenta and blue images
  device, soila_thresh = pcv.binary_threshold(soil_a, 124, 255, 'dark', device, args.debug)
  device, soilb_thresh = pcv.binary_threshold(soil_b, 148, 255, 'light', device, args.debug)

  # Join the thresholded saturation and blue-yellow images (OR)
  device, soil_ab = pcv.logical_or(soila_thresh, soilb_thresh, device, args.debug)
  device, soil_ab_cnt = pcv.logical_or(soila_thresh, soilb_thresh, device, args.debug)

  # Fill small objects
  device, soil_cnt = pcv.fill(soil_ab, soil_ab_cnt, 250, device, args.debug)

  # Median Filter
  #device, soil_mblur = pcv.median_blur(soil_fill, 5, device, args.debug)
  #device, soil_cnt = pcv.median_blur(soil_fill, 5, device, args.debug)

danforthcenter / plantcv / scripts / image_analysis / vis_sv / vis_sv_z500_L1.py View on Github

device, masked3 = pcv.apply_mask(masked2, kept_mask1, 'white', device, args.debug)
  device, masked_a1 = pcv.rgb2gray_lab(masked3, 'a', device, args.debug)
  device, masked_b1 = pcv.rgb2gray_lab(masked3, 'b', device, args.debug)
  device, maskeda_thresh1 = pcv.binary_threshold(masked_a1, 122, 255, 'dark', device, args.debug)
  device, maskedb_thresh1 = pcv.binary_threshold(masked_b1, 170, 255, 'light', device, args.debug)
  device, ab1 = pcv.logical_or(maskeda_thresh1, maskedb_thresh1, device, args.debug)
  device, ab_cnt1 = pcv.logical_or(maskeda_thresh1, maskedb_thresh1, device, args.debug)
  device, ab_fill1 = pcv.fill(ab1, ab_cnt1, 200, device, args.debug)

  
  device, roi2, roi_hierarchy2= pcv.define_roi(masked2,'rectangle', device, None, 'default', args.debug,True, 1900, 0,0,0)
  device, id_objects2,obj_hierarchy2 = pcv.find_objects(masked2, ab_fill, device, args.debug)
  device,roi_objects2, hierarchy2, kept_mask2, obj_area2 = pcv.roi_objects(masked2,'cutto',roi2,roi_hierarchy2,id_objects2,obj_hierarchy2,device, args.debug)
  device, masked4 = pcv.apply_mask(masked2, kept_mask2, 'white', device, args.debug)
  device, masked_a2 = pcv.rgb2gray_lab(masked4, 'a', device, args.debug)
  device, masked_b2 = pcv.rgb2gray_lab(masked4, 'b', device, args.debug)
  device, maskeda_thresh2 = pcv.binary_threshold(masked_a2, 122, 255, 'dark', device, args.debug)
  device, maskedb_thresh2 = pcv.binary_threshold(masked_b2, 170, 255, 'light', device, args.debug)
  device, ab2 = pcv.logical_or(maskeda_thresh2, maskedb_thresh2, device, args.debug)
  device, ab_cnt2 = pcv.logical_or(maskeda_thresh2, maskedb_thresh2, device, args.debug)
  device, ab_fill2 = pcv.fill(ab2, ab_cnt2, 200, device, args.debug)
  
  device, ab_cnt3 = pcv.logical_or(ab_fill1, ab_fill2, device, args.debug)
  device, masked3 = pcv.apply_mask(masked2, ab_cnt3, 'white', device, args.debug)
  
  # Identify objects
  device, id_objects3,obj_hierarchy3 = pcv.find_objects(masked2, ab_fill, device, args.debug)

  # Define ROI
  device, roi3, roi_hierarchy3= pcv.define_roi(masked2,'rectangle', device, None, 'default', args.debug,True, 525, 0,-500,-110)
 
  # Decide which objects to keep and combine with objects overlapping with black bars

danforthcenter / plantcv / scripts / dev / gehan_brachy / vis-nir-sv / vis_nir_sv_z3500_h2_e82_brachy_drought.py View on Github

# Threshold the blue image
  device, b_thresh = pcv.binary_threshold(b, 137, 255, 'light', device, args.debug)
  device, b_cnt = pcv.binary_threshold(b, 137, 255, 'light', device, args.debug)
  
  # Fill small objects
  #device, b_fill = pcv.fill(b_thresh, b_cnt, 10, device, args.debug)
  
  # Join the thresholded saturation and blue-yellow images
  device, bs = pcv.logical_and(s_mblur, b_cnt, device, args.debug)
  
  # Apply Mask (for vis images, mask_color=white)
  device, masked = pcv.apply_mask(img, bs, 'white', device, args.debug)
  
  # Convert RGB to LAB and extract the Green-Magenta and Blue-Yellow channels
  device, masked_a = pcv.rgb2gray_lab(masked, 'a', device, args.debug)
  device, masked_b = pcv.rgb2gray_lab(masked, 'b', device, args.debug)
  
  # Threshold the green-magenta and blue images
  device, maskeda_thresh = pcv.binary_threshold(masked_a, 127, 255, 'dark', device, args.debug)
  device, maskedb_thresh = pcv.binary_threshold(masked_b, 128, 255, 'light', device, args.debug)
  
  # Join the thresholded saturation and blue-yellow images (OR)
  device, ab = pcv.logical_or(maskeda_thresh, maskedb_thresh, device, args.debug)
  device, ab_cnt = pcv.logical_or(maskeda_thresh, maskedb_thresh, device, args.debug)
  
  # Fill small noise
  device, ab_fill1 = pcv.fill(ab, ab_cnt, 2, device, args.debug)
  
  # Dilate to join small objects with larger ones
  device, ab_cnt1=pcv.dilate(ab_fill1, 3, 2, device, args.debug)
  device, ab_cnt2=pcv.dilate(ab_fill1, 3, 2, device, args.debug)

danforthcenter / plantcv / scripts / dev / vis_sv_z2500_L2.py View on Github

# Threshold the blue image
  device, b_thresh = pcv.binary_threshold(b, 138, 255, 'light', device, args.debug)
  device, b_cnt = pcv.binary_threshold(b, 138, 255, 'light', device, args.debug)
  
  # Fill small objects
  device, b_fill = pcv.fill(b_thresh, b_cnt, 10, device, args.debug)
  
  # Join the thresholded saturation and blue-yellow images
  device, bs = pcv.logical_or(s_fill, b_fill, device, args.debug)
  
  # Apply Mask (for vis images, mask_color=white)
  device, masked = pcv.apply_mask(img, bs, 'white', device, args.debug)
  
  # Convert RGB to LAB and extract the Green-Magenta and Blue-Yellow channels
  device, masked_a = pcv.rgb2gray_lab(masked, 'a', device, args.debug)
  device, masked_b = pcv.rgb2gray_lab(masked, 'b', device, args.debug)
  
  # Threshold the green-magenta and blue images
  device, maskeda_thresh = pcv.binary_threshold(masked_a, 125, 255, 'dark', device, args.debug)
  device, maskedb_thresh = pcv.binary_threshold(masked_b, 133, 255, 'light', device, args.debug)
  
  # Join the thresholded saturation and blue-yellow images (OR)
  device, ab = pcv.logical_or(maskeda_thresh, maskedb_thresh, device, args.debug)
  device, ab_cnt = pcv.logical_or(maskeda_thresh, maskedb_thresh, device, args.debug)
  
  # Fill small objects
  device, ab_fill = pcv.fill(ab, ab_cnt, 10, device, args.debug)
  
  # Apply mask (for vis images, mask_color=white)
  device, masked2 = pcv.apply_mask(masked, ab_fill, 'white', device, args.debug)
  
  # Identify objects

How to use the plantcv.rgb2gray_lab function in plantcv

To help you get started, we’ve selected a few plantcv examples, based on popular ways it is used in public projects.

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