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Run on rgb only if no depth #24

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Run on rgb only if no depth #24

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51 changes: 51 additions & 0 deletions scripts/detectron_predictor/detectron_predictor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -97,6 +97,57 @@ def _get_catalog(self,catalog_file):
if(__debug__): print(traceback.format_exc())
raise Exception(e)
return data

def get_rgb_predictions_image(self, rgb_image, output_json_file_path='',prediction_output_dir='',image_file_name='',sample_no=1,fruit_type=FruitTypes.Strawberry):
rgb_image = rgb_image[:, :, :3].astype(np.uint8)
image_size = rgb_image.shape
image_size = tuple(reversed(image_size[:-1]))
save_json_file = True
try:
outputs = self.predictor(rgb_image)
predictions = outputs["instances"].to("cpu")
vis_aoc = AOCVisualizer(rgb_image,
metadata=self.metadata[0],
scale=self.scale,
instance_mode=self.instance_mode,
colours=self.colours,
category_ids=self.list_category_ids,
masks=self.masks,
bbox=self.bbox,
show_orientation=self.show_orientation,
fruit_type=fruit_type
)
start_time = datetime.now()
drawn_predictions = vis_aoc.draw_instance_predictions(outputs["instances"].to("cpu"))
end_time = datetime.now()
predicted_image = drawn_predictions.get_image()[:, :, ::-1].copy()

pred_image_dir = os.path.join(prediction_output_dir, 'predicted_images')
if not os.path.exists(pred_image_dir):
os.makedirs(pred_image_dir)

if (self.rename_pred_images):
f_name=f'img_{str(sample_no).zfill(6)}.png'
overlay_fName = os.path.join(pred_image_dir, f_name)
file_dir, f = os.path.split(output_json_file_path)
image_file_name = f_name
f_name = f'img_{str(sample_no).zfill(6)}.json'
output_json_file_path = os.path.join(file_dir, f_name)

else:
file_dir, f_name = os.path.split(image_file_name)
overlay_fName = os.path.join(pred_image_dir, f_name)
cv2.imwrite(overlay_fName, cv2.cvtColor(predicted_image, cv2.COLOR_BGR2RGB))
delta=str(end_time - start_time)
print(f"Predicted image saved in output folder for file {overlay_fName}, Duration: {delta}")
json_writer = JSONWriter(rgb_image, self.metadata[0])
categories_info=self.metadata[1] # category info is saved as second list
predicted_json_ann=json_writer.create_prediction_json(predictions, output_json_file_path, image_file_name,categories_info,image_size,1,save_json_file)
return predicted_json_ann,predicted_image,[]
except Exception as e:
logging.error(e)
if(__debug__): print(traceback.format_exc())
raise Exception(e)

def get_predictions_image(self, rgbd_image,output_json_file_path='',prediction_output_dir='',image_file_name='',sample_no=1,fruit_type=FruitTypes.Strawberry):

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11 changes: 10 additions & 1 deletion scripts/fruit_detection.py
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Original file line number Diff line number Diff line change
Expand Up @@ -163,7 +163,16 @@ def __init__(self, non_ros_config_path):
prediction_json_output_file = os.path.join(self.prediction_json_dir, filename)+'.json'
self.det_predictor.get_predictions_image(rgbd_image, prediction_json_output_file, self.prediction_output_dir, image_file_name, sample_no, self.fruit_type)
else:
self.get_logger().warn(f"Warning: No corresponding depth file: {corr_depth_file} for rgb file: {rgb_file}")
self.get_logger().warn(f"Warning: No corresponding depth file: {corr_depth_file} for rgb file: {rgb_file}.\nPredicting using rgb only.")
image_file_name=os.path.join(self.image_dir, rgb_file)
rgb_image = cv2.imread(image_file_name) # bgr8
filename, extension = os.path.splitext(rgb_file)
if (self.prediction_json_dir!=""):
os.makedirs(self.prediction_json_dir, exist_ok=True)
prediction_json_output_file = os.path.join(self.prediction_json_dir, filename)+'.json'

self.det_predictor.get_rgb_predictions_image(rgb_image, prediction_json_output_file, self.prediction_output_dir, image_file_name, sample_no, self.fruit_type)

sample_no += 1

def compute_pose2d(self, annotation_id, pose_dict):
Expand Down