waqarsqureshi
commented
2 years ago I found a solution. just use the opencv findContour function. the code is below `# Copyright (C) 2020 Intel Corporation #
SPDX-License-Identifier: MIT
import os import cv2 import numpy as np from skimage.measure import approximate_polygon, find_contours from model_loader import ModelLoader
class ModelHandler: def init(self, labels): base_dir = os.path.abspath(os.environ.get("MODEL_PATH", "/opt/nuclio/open_model_zoo/intel/semantic-segmentation-adas-0001/FP32")) model_xml = os.path.join(base_dir, "semantic-segmentation-adas-0001.xml") model_bin = os.path.join(base_dir, "semantic-segmentation-adas-0001.bin") self.model = ModelLoader(model_xml, model_bin) self.labels = labels
def infer(self, image, threshold):
output_layer = self.model.infer(image)
results = []
mask = output_layer[0, 0, :, :]
width, height = mask.shape
for i in range(len(self.labels)):
mask_by_label = np.zeros((width, height), dtype=np.uint8)
mask_by_label = ((mask == float(i)) * 255).astype(np.uint8)
mask_by_label = cv2.resize(mask_by_label,
dsize=(image.width, image.height),
interpolation=cv2.INTER_NEAREST)
#contours = find_contours(mask_by_label, 0.5)
contours, hierarchy = cv2.findContours(mask_by_label, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
for contour in contours:
contour = np.flip(contour, axis=1)
#contour = approximate_polygon(contour, tolerance=2.5)
if len(contour) < 3:
continue
results.append({
"confidence": None,
"label": self.labels.get(i, "unknown"),
"points": contour.ravel().tolist(),
"type": "polygon",
})
return results`
In the picture below we can see the polygon drawn automatically by the function approximate_polygon, which has two input find contours from find_countours and the tolerance. The tolerance controls the number of points in the polygons while the contour is the point for the polygon to draw.
As we can see clearly the road is not identified properly. It should cover all the way down touching the ends of the image. This happens with all of the images and it surely is a limitation in the approximate polygon method or find_contour method. When the same mask is generated using the OpenVino in an offline model the mask covers the whole road. below is the expected output from the software.
Steps to Reproduce (for bugs)