Restored plots to chart_reg and fixed a bug

slider/chart_reg.py

@@ -42,6 +42,15 @@ def register_chart_to_slide(chart, slide, slide_res, out, config=None):
     rlevel = config['slide']['resolution_level']
     boundary_key = config['chart']['boundary_key']
 
+    # set global variables required for summary plots
+    plots = config['general']['plots']
+
+    global DO_PLOTS
+    DO_PLOTS = plots
+
+    global OUTDIR
+    OUTDIR = out
+        
     # load chart
     contour, cells = neurolucida.read(chart)
 
@@ -53,7 +62,7 @@ def register_chart_to_slide(chart, slide, slide_res, out, config=None):
 
     # initial scaling based on boundng boxes
     edge_crds = contour[boundary_key][:, :2] * [1, -1]
-    init = _init_scale(img, slide_res, edge_crds, verbose=True, plots=False)
+    init = _init_scale(img, slide_res, edge_crds, verbose=True)
     print(init)
     print(
         f'Rotation: {init.rotation}, Translation: {init.translation}, Scale: {init.scale}, Shear: {init.shear}')
@@ -98,18 +107,15 @@ def _refine_edge_coord(img, img_res, edge_coords, normals):
     """
 
     # calculate normal line (to edge_coords)
-    edge_x, edge_y = np.round(edge_coords.T).astype(int)
+    edge_x, edge_y = edge_coords.T
     nrml_x, nrml_y = normals.T
 
-    line_smpl = np.arange(-20, 20) * img_res
+    # line_smpl = np.arange(-10, 10) * img_res
+    line_smpl = np.linspace(-0.03, 0.15, 20)
 
     line_x = edge_x[:, np.newaxis] + nrml_x[:, np.newaxis] * line_smpl
     line_y = edge_y[:, np.newaxis] + nrml_y[:, np.newaxis] * line_smpl
-
-    line_x = np.round(line_x / img_res).astype(int)
-    line_y = np.round(line_y / img_res).astype(int)
     
-
     # find threshold for background
     image = rgb2gray(img)
     threshold_value = filters.threshold_otsu(image)
@@ -129,22 +135,63 @@ def _refine_edge_coord(img, img_res, edge_coords, normals):
     p = p[ridx]
 
     cc0 = (cc == p.label)
-    # plt.imshow(cc0)
+
+    if DO_PLOTS:
+        fig, ax = plt.subplots(figsize=(20, 30))
+
+        extent = np.array([0, img.shape[1], img.shape[0], 0]) * img_res
+        ax.imshow(cc0, extent=extent)
+
+        for line_x0, line_y0 in zip(line_x, line_y):
+            ax.plot(line_x0, line_y0, 'b.')
+
+        ax.plot(edge_x, edge_y, 'r.')
+
+        ax.set_xlabel('mm')
+        ax.set_ylabel('mm')
+        ax.set_title('Largest connected component + normals')
+        
+        fig.savefig(f'{OUTDIR}/normals.png', bbox_inches='tight', dpi=300)
+
+
+    # sample image along normal line
+
+    line_x = np.round(line_x / img_res).astype(int)
+    line_y = np.round(line_y / img_res).astype(int)
 
     line_int = cc0[line_y, line_x]
 
     min_idx = np.argmax(np.diff(line_int, axis=-1), axis=-1)
 
     refined_edge_coords = np.stack([
-        line_x[np.arange(min_idx.size), min_idx],
-        line_y[np.arange(min_idx.size), min_idx],
+        line_x[np.arange(min_idx.size), min_idx] * img_res,
+        line_y[np.arange(min_idx.size), min_idx] * img_res,
     ], axis=-1)
 
+    # TODO: plot edge_coords + refined_edge_coords
+    if DO_PLOTS:
+        fig, ax = plt.subplots(figsize=(20, 30))
+
+        extent = np.array([0, img.shape[1], img.shape[0], 0]) * img_res
+        ax.imshow(img, extent=extent)
+
+        ax.plot(edge_x, edge_y, 'r.-')
+        ax.plot(refined_edge_coords[:, 0], refined_edge_coords[:, 1], 'g.-')
+
+        ax.set_xlabel('mm')
+        ax.set_ylabel('mm')
+        # ax.set_title('edge_co')
+
+        ax.legend(['edge_coords', 'refined_edge_coords'])
+        
+        fig.savefig(f'{OUTDIR}/refined_coords.png', bbox_inches='tight', dpi=300)
+
+
     return refined_edge_coords * img_res
 
 
 
-def _img_props(img, img_resolution, verbose=False, plots=False):
+def _img_props(img, img_resolution, verbose=False):
 
     # convert to grayscale
     image = rgb2gray(img)
@@ -175,24 +222,31 @@ def _img_props(img, img_resolution, verbose=False, plots=False):
         (bbox[1] + bbox[3])/2,
     )
 
-    # TODO: make plots work again
-    # if plots:
+    if DO_PLOTS:
 
-    #     plt.imshow(cc == p.label)
-    #     plt.colorbar()
+        fig, ax = plt.subplots()
+        extent = np.array([0, img.shape[1], img.shape[0], 0]) * img_resolution
 
-    #     rect = patches.Rectangle(
-    #         (bbox[1], bbox[0]),
-    #         bbox[3]-bbox[1],
-    #         bbox[2]-bbox[0],
-    #         linewidth=1,
-    #         edgecolor='r',
-    #         facecolor='none'
-    #     )
-    #     plt.gca().add_patch(rect)
+        im = ax.imshow(cc == p.label, extent=extent)
+        fig.colorbar(im)
 
-    #     plt.plot(centroid[1], centroid[0], 'ro')
-    #     plt.show()
+        rect = patches.Rectangle(
+            (bbox[1], bbox[0]),
+            bbox[3]-bbox[1],
+            bbox[2]-bbox[0],
+            linewidth=1,
+            edgecolor='r',
+            facecolor='none'
+        )
+        ax.add_patch(rect)
+
+        ax.plot(centroid[1], centroid[0], 'ro')
+        
+        ax.set_xlabel('mm')
+        ax.set_ylabel('mm')
+        ax.set_title('Image bounding box')
+        
+        fig.savefig(f'{OUTDIR}/image_bounding_box.png', bbox_inches='tight', dpi=150)
 
     return {
         'bbox': bbox, 
@@ -201,7 +255,7 @@ def _img_props(img, img_resolution, verbose=False, plots=False):
         }
 
 
-def _pnt_props(pnts, verbose=False, plots=False):
+def _pnt_props(pnts, verbose=False):
 
     x = pnts[:, 0]
     y = pnts[:, 1]
@@ -222,10 +276,13 @@ def _pnt_props(pnts, verbose=False, plots=False):
         print(f'bbox={bbox}')
         print(f'centroid={centroid}')
 
-    if plots:
-        plt.plot(x, y, 'b.')
-        plt.axis('equal')
-        plt.gca().invert_yaxis()
+    if DO_PLOTS:
+
+        fig, ax = plt.subplots()
+
+        ax.plot(x, y, 'b.')
+        ax.axis('equal')
+        ax.invert_yaxis()
 
         rect = patches.Rectangle(
             (bbox[1], bbox[0]),
@@ -235,15 +292,18 @@ def _pnt_props(pnts, verbose=False, plots=False):
             edgecolor='r',
             facecolor='none'
         )
-
-        plt.gca().add_patch(rect)
+        ax.add_patch(rect)
 
         plt.plot(centroid[1], centroid[0], 'ro')
 
+        ax.set_title('Chart bounding box')
+        
+        fig.savefig(f'{OUTDIR}/chart_bounding_box.png', bbox_inches='tight', dpi=150)
+
     return {'bbox': bbox, 'bbox_centroid': centroid, 'shape': (bbox[2]-bbox[0], bbox[3]-bbox[1])}
 
 
-def _init_scale(img, img_resolution, crd, verbose=False, plots=False):
+def _init_scale(img, img_resolution, crd, verbose=False):
 
     img_p = _img_props(img, img_resolution)
     crd_p = _pnt_props(crd)

slider/resources/chart.yaml

+general:
+    # genarate summary plots of each stage
+    plots: True
 chart:
     # key for the contour to use for aligning with image 
     boundary_key: outline