move subclasses of stitcher back to stitcher module.

tests/test_core.py

@@ -1,24 +1,6 @@
 import os
 
-import cv2
-import numpy as np
 import pytest
-from numpy import testing as npt
-
-import bb_stitcher.picking.picker
-import bb_stitcher.helpers as helpers
-import bb_stitcher.stitcher as stitcher
-
-
-def draw_marks(img, pts, color=(0, 0, 255), marker_types=cv2.MARKER_CROSS):
-    img_m = np.copy(img)
-    if len(img_m.shape) == 2:
-        img_m = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
-    pts = pts.astype(int)
-    for pt in pts:
-        cv2.drawMarker(img_m, tuple(pt), color, markerType=marker_types,
-                       markerSize=40, thickness=5)
-    return img_m
 
 
 @pytest.fixture
@@ -27,142 +9,3 @@ def outdir(main_outdir):
     if not os.path.exists(out_path):
         os.makedirs(out_path)
     return out_path
-
-
-@pytest.fixture
-def fb_stitcher(config):
-    fbs = stitcher.FeatureBasedStitcher(config)
-    return fbs
-
-
-def test_get_default_config():
-    config = helpers.get_default_config()
-
-    config_set = {
-        'Rectificator',
-        'FeatureBasedStitcher',
-        'SURF',
-        'FeatureMatcher'}
-    assert set(config.sections()) == config_set
-
-
-def test_get_default_debug_config():
-    deb_config = helpers.get_default_debug_config()
-    assert 'loggers' in deb_config
-
-
-"""
-Test for feature based Stitcher.
-"""
-
-
-def test_calc_feature_mask():
-    target_mask_left = np.array(
-        [[0, 0, 0],
-         [0, 0, 0],
-         [0, 0, 0],
-         [0, 255, 255],
-         [0, 255, 255],
-         [0, 255, 255],
-         [0, 255, 255],
-         [0, 0, 0],
-         ], np.uint8)
-    target_mask_right = np.array(
-        [[0, 0, 0],
-         [0, 0, 0],
-         [0, 0, 0],
-         [255, 255, 0],
-         [255, 255, 0],
-         [255, 255, 0],
-         [255, 255, 0],
-         [0, 0, 0],
-         ], np.uint8)
-    mask_left, mask_right = stitcher.FeatureBasedStitcher._calc_feature_mask(
-        (3, 8), (3, 8), 2, 3, 1)
-    npt.assert_equal(mask_left, target_mask_left)
-    npt.assert_equal(mask_right, target_mask_right)
-
-
-def test_fb_estimate_transform(fb_stitcher, left_img, right_img, not_to_bee):
-    # provoke no finding of transformation
-    fb_stitcher.estimate_transform(left_img['img'], not_to_bee)
-    assert fb_stitcher.homo_left is None and fb_stitcher.homo_right is None
-
-    # find transformation
-    fb_stitcher.estimate_transform(left_img['img'], right_img['img'], 90, -90)
-    assert fb_stitcher.homo_left is not None and fb_stitcher.homo_right is not None
-
-
-@pytest.mark.slow
-def test_overall_fb_stitching(fb_stitcher, left_img, right_img, outdir):
-    fb_stitcher.estimate_transform(left_img['img'], right_img['img'], 90, -90)
-    assert fb_stitcher.homo_left is not None and fb_stitcher.homo_right is not None
-    pano = fb_stitcher.compose_panorama(
-        left_img['img_w_detections'], right_img['img_w_detections'])
-    detections_left_mapped = fb_stitcher.map_left_points(left_img['detections'])
-    detections_right_mapped = fb_stitcher.map_right_points(right_img['detections'])
-    pano = draw_marks(pano, detections_left_mapped)
-    pano = draw_marks(pano, detections_right_mapped)
-
-    out = os.path.join(outdir, 'panorama_fb_w_detections.jpg')
-    cv2.imwrite(out, pano)
-
-
-"""
-Test for rectangle Stitcher.
-"""
-
-
-def test_rect_stitcher_estimate_transform(left_img, right_img, outdir, config,
-                                          monkeypatch):
-    def mockreturn(myself, image_list, all):
-        left_points = np.array([
-            [88.91666412, 3632.6015625],
-            [2760.26855469, 3636.70849609],
-            [2726.26708984, 363.4861145],
-            [93.88884735, 371.98330688]], dtype=np.float32)
-        right_points = np.array([
-            [181.49372864, 3687.71582031],
-            [2903.44042969, 3723.99926758],
-            [2921.27368164, 458.77352905],
-            [255.66642761, 431.24780273]], dtype=np.float32)
-        return left_points, right_points
-    monkeypatch.setattr(bb_stitcher.picking.picker.PointPicker, 'pick', mockreturn)
-    # print(left_points)
-    rt_stitcher = stitcher.RectangleStitcher(config)
-    rt_stitcher.estimate_transform(
-        left_img['img'], right_img['img'], 90, -90)
-    assert rt_stitcher.homo_left is not None
-    assert rt_stitcher.homo_right is not None
-    assert rt_stitcher.pano_size is not None
-
-
-@pytest.mark.slow
-def test_overall_rt_stitching(left_img, right_img, outdir, config, monkeypatch):
-    def mockreturn(myself, image_list, all):
-        left_points = np.array([
-            [88.91666412, 3632.6015625],
-            [2760.26855469, 3636.70849609],
-            [2726.26708984, 363.4861145],
-            [93.88884735, 371.98330688]], dtype=np.float32)
-        right_points = np.array([
-            [181.49372864, 3687.71582031],
-            [2903.44042969, 3723.99926758],
-            [2921.27368164, 458.77352905],
-            [255.66642761, 431.24780273]], dtype=np.float32)
-        return left_points, right_points
-    monkeypatch.setattr(bb_stitcher.picking.picker.PointPicker, 'pick', mockreturn)
-    rt_stitcher = stitcher.RectangleStitcher(config)
-    rt_stitcher.estimate_transform(left_img['img'], right_img['img'], 90, -90)
-    assert rt_stitcher.homo_left is not None
-    assert rt_stitcher.homo_right is not None
-    assert rt_stitcher.pano_size is not None
-    pano = rt_stitcher.compose_panorama(
-        left_img['img_w_detections'], right_img['img_w_detections'])
-    detections_left_mapped = rt_stitcher.map_left_points(left_img['detections'])
-    detections_right_mapped = rt_stitcher.map_right_points(right_img['detections'])
-    pano = draw_marks(pano, detections_left_mapped)
-    pano = draw_marks(pano, detections_right_mapped)
-
-    out = os.path.join(outdir, 'panorama_rt_w_detections.jpg')
-    cv2.imwrite(out, pano)

tests/test_helpers.py

@@ -184,3 +184,19 @@ def test_get_ratio_px_to_mm():
     distance_mm = 25
     px_to_mm = helpers.get_ratio_px_to_mm(start_point, end_point, distance_mm)
     assert px_to_mm == 0.5
+
+
+def test_get_default_config():
+    config = helpers.get_default_config()
+
+    config_set = {
+        'Rectificator',
+        'FeatureBasedStitcher',
+        'SURF',
+        'FeatureMatcher'}
+    assert set(config.sections()) == config_set
+
+
+def test_get_default_debug_config():
+    deb_config = helpers.get_default_debug_config()
+    assert 'loggers' in deb_config

tests/test_stitcher.py

@@ -2,8 +2,8 @@
 
 import cv2
 import numpy as np
-import numpy.testing as npt
 import pytest
+import numpy.testing as npt
 
 import bb_stitcher.helpers as helpers
 import bb_stitcher.picking.picker
@@ -199,3 +199,110 @@ def mockreturn(myself, image_list, all):
     monkeypatch.setattr(bb_stitcher.picking.picker.PointPicker, 'pick', mockreturn)
     monkeypatch.setitem(__builtins__, 'input', lambda x: "348")
     super_stitcher._calc_image_to_world_mat(panorama)
+
+
+def test_calc_feature_mask():
+    target_mask_left = np.array(
+        [[0, 0, 0],
+         [0, 0, 0],
+         [0, 0, 0],
+         [0, 255, 255],
+         [0, 255, 255],
+         [0, 255, 255],
+         [0, 255, 255],
+         [0, 0, 0],
+         ], np.uint8)
+    target_mask_right = np.array(
+        [[0, 0, 0],
+         [0, 0, 0],
+         [0, 0, 0],
+         [255, 255, 0],
+         [255, 255, 0],
+         [255, 255, 0],
+         [255, 255, 0],
+         [0, 0, 0],
+         ], np.uint8)
+    mask_left, mask_right = stitcher.FeatureBasedStitcher._calc_feature_mask(
+        (3, 8), (3, 8), 2, 3, 1)
+    npt.assert_equal(mask_left, target_mask_left)
+    npt.assert_equal(mask_right, target_mask_right)
+
+
+def test_fb_estimate_transform(fb_stitcher, left_img, right_img, not_to_bee):
+    # provoke no finding of transformation
+    fb_stitcher.estimate_transform(left_img['img'], not_to_bee)
+    assert fb_stitcher.homo_left is None and fb_stitcher.homo_right is None
+
+    # find transformation
+    fb_stitcher.estimate_transform(left_img['img'], right_img['img'], 90, -90)
+    assert fb_stitcher.homo_left is not None and fb_stitcher.homo_right is not None
+
+
+@pytest.mark.slow
+def test_overall_fb_stitching(fb_stitcher, left_img, right_img, outdir):
+    fb_stitcher.estimate_transform(left_img['img'], right_img['img'], 90, -90)
+    assert fb_stitcher.homo_left is not None and fb_stitcher.homo_right is not None
+    pano = fb_stitcher.compose_panorama(
+        left_img['img_w_detections'], right_img['img_w_detections'])
+    detections_left_mapped = fb_stitcher.map_left_points(left_img['detections'])
+    detections_right_mapped = fb_stitcher.map_right_points(right_img['detections'])
+    pano = draw_marks(pano, detections_left_mapped)
+    pano = draw_marks(pano, detections_right_mapped)
+
+    out = os.path.join(outdir, 'panorama_fb_w_detections.jpg')
+    cv2.imwrite(out, pano)
+
+
+def test_rect_stitcher_estimate_transform(left_img, right_img, outdir, config,
+                                          monkeypatch):
+    def mockreturn(myself, image_list, all):
+        left_points = np.array([
+            [88.91666412, 3632.6015625],
+            [2760.26855469, 3636.70849609],
+            [2726.26708984, 363.4861145],
+            [93.88884735, 371.98330688]], dtype=np.float32)
+        right_points = np.array([
+            [181.49372864, 3687.71582031],
+            [2903.44042969, 3723.99926758],
+            [2921.27368164, 458.77352905],
+            [255.66642761, 431.24780273]], dtype=np.float32)
+        return left_points, right_points
+    monkeypatch.setattr(bb_stitcher.picking.picker.PointPicker, 'pick', mockreturn)
+    # print(left_points)
+    rt_stitcher = stitcher.RectangleStitcher(config)
+    rt_stitcher.estimate_transform(
+        left_img['img'], right_img['img'], 90, -90)
+    assert rt_stitcher.homo_left is not None
+    assert rt_stitcher.homo_right is not None
+    assert rt_stitcher.pano_size is not None
+
+
+@pytest.mark.slow
+def test_overall_rt_stitching(left_img, right_img, outdir, config, monkeypatch):
+    def mockreturn(myself, image_list, all):
+        left_points = np.array([
+            [88.91666412, 3632.6015625],
+            [2760.26855469, 3636.70849609],
+            [2726.26708984, 363.4861145],
+            [93.88884735, 371.98330688]], dtype=np.float32)
+        right_points = np.array([
+            [181.49372864, 3687.71582031],
+            [2903.44042969, 3723.99926758],
+            [2921.27368164, 458.77352905],
+            [255.66642761, 431.24780273]], dtype=np.float32)
+        return left_points, right_points
+    monkeypatch.setattr(bb_stitcher.picking.picker.PointPicker, 'pick', mockreturn)
+    rt_stitcher = stitcher.RectangleStitcher(config)
+    rt_stitcher.estimate_transform(left_img['img'], right_img['img'], 90, -90)
+    assert rt_stitcher.homo_left is not None
+    assert rt_stitcher.homo_right is not None
+    assert rt_stitcher.pano_size is not None
+    pano = rt_stitcher.compose_panorama(
+        left_img['img_w_detections'], right_img['img_w_detections'])
+    detections_left_mapped = rt_stitcher.map_left_points(left_img['detections'])
+    detections_right_mapped = rt_stitcher.map_right_points(right_img['detections'])
+    pano = draw_marks(pano, detections_left_mapped)
+    pano = draw_marks(pano, detections_right_mapped)
+
+    out = os.path.join(outdir, 'panorama_rt_w_detections.jpg')
+    cv2.imwrite(out, pano)