dan
426a18f342
- Remove 257 redundant per-definition comment stubs across the package - Drop dead nonlocal declarations in autoslicer_detection.py - Document the swapped flag and swap_left_right in architecture docs - Remove unsupported 'legacy override' claims from autotune/runtime docs
93 lines
2.8 KiB
Python
93 lines
2.8 KiB
Python
import cv2
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import numpy as np
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from .autoslicer_detection import AutoslicerDetectionMixin
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from .autoslicer_feedback import AutoslicerFeedbackMixin
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from .params import AutoslicerParams
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class Autoslicer(AutoslicerFeedbackMixin, AutoslicerDetectionMixin):
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MAX_RETURNED_BOXES = 400
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MAX_FEEDBACK_ENTRIES = 500
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AUTOTUNE_PARAM_KEYS = (
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"detect_pipeline",
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"clahe_clip",
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"gaussian",
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"bw_method",
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"bw_thresh",
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"bw_gauss",
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"bw_adaptive_c",
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"invert_mode",
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"morph_op",
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"contour_approx_pct",
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"bbox_min_size",
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"bbox_max_size",
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"bbox_fill_thresh",
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"aspect_ratio_min",
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"aspect_ratio_max",
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"border_ignore",
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"iou_merge_thresh",
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"dilate_kernel",
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)
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def __init__(self, params=None):
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self.image = None
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self.image_gray = None
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self.image_path = None
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self.abort_flag = False
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self.params = None
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self.set_params(params)
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self.feedback_entries = self.load_feedback_entries()
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def set_params(self, params):
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self.params = params if params is not None else AutoslicerParams()
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def image_loaded(self):
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return self.image is not None
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def load_image(self, image_path):
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self.image_path = image_path
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self.image = cv2.imread(image_path)
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self.image_gray = cv2.cvtColor(self.image, cv2.COLOR_BGR2GRAY)
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def abort_operation(self):
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self.abort_flag = True
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def update_status(self, update_status_callback, text):
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if update_status_callback is not None:
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update_status_callback(text)
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def save_slice(self, hull_quad, out_path, imwrite_params=None):
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hull_quad = np.array(hull_quad, dtype=np.float32).reshape(4, 2)
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# Input order is assumed [top-left, top-right, bottom-right, bottom-left].
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top_w = np.linalg.norm(hull_quad[1] - hull_quad[0])
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bottom_w = np.linalg.norm(hull_quad[2] - hull_quad[3])
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left_h = np.linalg.norm(hull_quad[3] - hull_quad[0])
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right_h = np.linalg.norm(hull_quad[2] - hull_quad[1])
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out_w = max(1, int(round(max(top_w, bottom_w))))
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out_h = max(1, int(round(max(left_h, right_h))))
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dst_quad = np.array(
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[
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[0.0, 0.0],
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[float(out_w - 1), 0.0],
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[float(out_w - 1), float(out_h - 1)],
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[0.0, float(out_h - 1)],
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],
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dtype=np.float32,
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)
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perspective_m = cv2.getPerspectiveTransform(hull_quad, dst_quad)
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warped_img = cv2.warpPerspective(
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self.image,
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perspective_m,
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(out_w, out_h),
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flags=cv2.INTER_CUBIC,
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)
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if imwrite_params is None:
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cv2.imwrite(out_path, warped_img)
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else:
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cv2.imwrite(out_path, warped_img, imwrite_params)
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