diff --git a/src/client.py b/src/client.py
index 65d83752f09889e0fcdd9d87dee0ea1f5354fa6c..fbb44f6b886a2bb818f4b5f611af6797ee9789cc 100755
--- a/src/client.py
+++ b/src/client.py
@@ -11,7 +11,7 @@ import logging #日志模块
# values over max (and under min) will be clipped
MAX_X = 2400
MAX_Y = 1200
-MIN_Z = -460 # TODO test this one!
+MAX_Z = 469 # TODO test this one!
def coord(x, y, z):
return {"kind": "coordinate", "args": {"x": x, "y": y, "z": z}} # 返回json 嵌套对象
@@ -66,7 +66,7 @@ class FarmbotClient(object):
def move(self, x, y, z):
x = clip(x, 0, MAX_X)
y = clip(y, 0, MAX_Y)
- z = clip(z, MIN_Z, 0)
+ z = clip(z, 0, MAX_Z)
status_ok = self._blocking_request(move_request(x, y, z)) # 发请求
logging.info("MOVE (%s,%s,%s) [%s]", x, y, z, status_ok) #存日志，包括执行了什么“move x y z +返回值 ”
diff --git a/src/detect.py b/src/detect.py
index ea1c2dc85989052f919b867f52007b525aab6e11..5f3296376fb6e2aa708db354c7fd55e175fb0cd0 100644
--- a/src/detect.py
+++ b/src/detect.py
@@ -125,10 +125,6 @@ def detect(args: Namespace)-> None:
darknet.print_detections(detections, args.ext_output)
fps = int(1/(time.time() - prev_time))
print("FPS: {}".format(fps))
- if not args.dont_show:
- cv2.imshow('Inference', resized_image)
- if cv2.waitKey() & 0xFF == ord('q'):
- break
index += 1
@@ -143,11 +139,9 @@ if __name__ == "__main__":
help="number of images to be processed at the same time")
parser.add_argument("--weights", default="../weights/yolov3-vattenhallen_best.weights",
help="yolo weights path")
- parser.add_argument("--dont_show", action='store_true',
- help="windown inference display. For headless systems")
- parser.add_argument("--ext_output", action='store_true',
+ parser.add_argument("--ext_output", action='store_true', default=True,
help="display bbox coordinates of detected objects")
- parser.add_argument("--save_labels", action='store_true',
+ parser.add_argument("--save_labels", action='store_true', default=True,
help="save detections bbox for each image in yolo format")
parser.add_argument("--config_file", default="../cfg/yolov3-vattenhallen-test.cfg",
help="path to config file")
diff --git a/src/location.py b/src/location.py
index 3cde737a785b17b3cd182438d6ec4259d08555a1..a9375b84dbbb4ded7fdec3647687408fca350369 100644
--- a/src/location.py
+++ b/src/location.py
@@ -98,12 +98,9 @@ def read_locations(locations_path: Path) -> Optional[ndarray]:
return None
number_files = len(listdir(locations_path))
- if number_files > 1:
+ if number_files != 1:
_LOG.error('More than one file of locations found the {}'.format(locations_path))
- raise FileExistsError
- elif number_files == 0:
- _LOG.error('No file of locations found the {}'.format(locations_path))
- raise FileNotFoundError
+ return None
locations_file = Path(locations_path, [file for file in listdir(locations_path)][0])
if not locations_file.suffix.lstrip('.') in _LOCATIONS_EXTENSIONS:
@@ -167,15 +164,13 @@ def cal_location(args: Namespace) -> ndarray:
main function for this script
'''
cam_offset, gripper_offset = read_offsets(args.offset)
- K_matrix = load_cam_matrix(args.camera_matrix)
- list_location = read_locations(args.locations) # 如果没有文件，会报错
+ K_matrix = load_cam_matrix(args.camera_matrix)
+ list_location = read_locations(args.locations)
# iterate over each annotation file
_LOG.info('Global coordinate calculation begins.')
list_annotations = listdir(args.annotations)
# sort by chronological order / specific for the filename on Ziliang's PC, change if other names
- time_label = lambda x: int(x.split('_')[1]+x.split('_')[2]
- +x.split('_')[3]+x.split('_')[4])
- list_annotations.sort(key=time_label)
+ list_annotations.sort()
# read annotations
for index_photo, annotation_file in enumerate(list_annotations):
filepath = Path(args.annotations, annotation_file)
@@ -214,6 +209,7 @@ def cal_location(args: Namespace) -> ndarray:
list_location[index_photo], cam_offset, gripper_offset)
list_global_coordinate.append([category, global_x, global_y, confidence])
_LOG.debug(list_global_coordinate[-1])
+
_LOG.info('Global coordinate calculation is done.')
return array(list_global_coordinate)
diff --git a/src/main.py b/src/main.py
index 0cae31e4380970b8f97a83b64aa79859858b1fc3..c68b26834577376f28ee6adbdeb8bf66f9ee69db 100644
--- a/src/main.py
+++ b/src/main.py
@@ -17,10 +17,10 @@ from move import *
from detect import *
from location import *
-_Log = getLogger(__name__)
+_LOG = getLogger(__name__)
-GRIP_Z = -200 # measure!
-SCAN_Z = -100
+GRIP_Z = 468 # measure!
+SCAN_Z = 0
ORIGIN_X = 0
ORIGIN_Y = 0
ORIGIN_Z = 0
@@ -34,13 +34,12 @@ def remove_overlap(table_coordinate:DataFrame, tolerance=50.00)->DataFrame:
:param table_coordinate: pandas dataframe that each row corresponds to a target [class, x, y, confidence]
:param tolerance: a distance threshold
'''
- # 这又要求重写前面的了，加入 probability
num_coordinates, num_col = table_coordinate.shape
for i in range(num_coordinates-1):
x, y, confidence = table_coordinate.loc[i, ['x','y', 'confidence']]
for j in range(i+1, num_coordinates):
x_j, y_j, confidence_j = table_coordinate.loc[j, ['x','y', 'confidence']]
- distance = sqrt((x-x_j)*(x-x_j)+(y-y_j)*(y-y_j)) # 用map优化？
+ distance = sqrt((float(x)-float(x_j))*(float(x)-float(x_j)) + (float(y)-float(y_j))*(float(y)-float(y_j)))
if distance <= tolerance:
if confidence < confidence_j:
table_coordinate.drop(i)
@@ -62,19 +61,29 @@ def remove_temp(path: Path)-> None:
def main(args: Namespace):
+ # clean temporary files
+ remove_temp(args.input)
+ remove_temp(args.locations)
+ remove_temp(args.annotations)
# start from the origin
- simple_move(0, 0, 0)
+ simple_move(ORIGIN_X, ORIGIN_Y, ORIGIN_Z)
+ _LOG.info("Go back to the origin")
# scan
- scan(flag=False)
+ scan(args.photo, args.locations, flag=False)
+ _LOG.info("Scan the planting bed")
# detect
detect(args)
+ _LOG.info("Detection is done")
# calculate locations
list_global_coordinate = cal_location(args)
+ _LOG.info("Global coordinate calculation is done.")
# choose class
table_global_coordinate = DataFrame(list_global_coordinate, columns=['class', 'x', 'y', 'confidence'])
# remove overlap
+ print(table_global_coordinate)
table_global_coordinate = remove_overlap(table_global_coordinate)
goal_class = table_global_coordinate[table_global_coordinate['class']==args.category]
+ _LOG.info("Choose {}".format(args.category))
# if there is no desiered class of plants
if goal_class.empty:
_LOG.info("There is no {}".format(args.category))
@@ -89,10 +98,6 @@ def main(args: Namespace):
# go back to the orgin
simple_move(x, y, GRIP_Z, False)
gripper_open()
- # clean temporary files if all the previous step work
- remove_temp(args.input)
- remove_temp(args.locations)
- remove_temp(args.annotations)
return
@@ -100,6 +105,14 @@ def main(args: Namespace):
if __name__ == '__main__':
parser = ArgumentParser(description="YOLOv3 detection on Farmbot")
+ # parsers for move
+ parser.add_argument(
+ '-p',
+ '--photo',
+ type=Path,
+ default="../img",
+ help='Mode for FarmBot, 1 for simple move with an assigned detination, 2 for scaning'
+ )
# parsers for detect
parser.add_argument("--input", type=str, default="../img",
help="image source. It can be a single image, a"
@@ -110,11 +123,9 @@ if __name__ == '__main__':
help="number of images to be processed at the same time")
parser.add_argument("--weights", default="../weights/yolov3-vattenhallen_best.weights",
help="yolo weights path")
- parser.add_argument("--dont_show", action='store_true',
- help="windown inference display. For headless systems")
- parser.add_argument("--ext_output", action='store_true',
+ parser.add_argument("--ext_output", action='store_true', default=True,
help="display bbox coordinates of detected objects")
- parser.add_argument("--save_labels", action='store_true',
+ parser.add_argument("--save_labels", action='store_true', default=True,
help="save detections bbox for each image in yolo format")
parser.add_argument("--config_file", default="../cfg/yolov3-vattenhallen-test.cfg",
help="path to config file")
@@ -126,7 +137,7 @@ if __name__ == '__main__':
parser.add_argument(
'-ca',
'--category',
- type=str,
+ type=int,
help='Choose the class of fruits to be picked up. There are tomato, mushroom,\
potato, carrot, beetroot, zucchini, hand'
)
diff --git a/src/move.py b/src/move.py
index 77788f67bed9f5a62615d43ef5549ac4c917933e..3768b918c06a894d58bd0311faac64012f0eed35 100644
--- a/src/move.py
+++ b/src/move.py
@@ -39,7 +39,8 @@ class Opts:
self.flag = flag
-def scan(img_path: Path, min_x=0, max_x=1300, min_y=0, max_y=1000, delta=500, offset=0, flag=True) -> List: #里面的数字需要重新测量
+def scan(img_path: Path, location_path: Path, # smaller delta
+ min_x=0, max_x=1300, min_y=0, max_y=1000, delta=1000, offset=0, flag=True) -> List: #里面的数字需要重新测量
'''
scan the bed at a certain height, first move along x axis, then y, like a zig zag;
Taking pictures and record the location of the camera that corresponds to the picture
@@ -77,7 +78,11 @@ def scan(img_path: Path, min_x=0, max_x=1300, min_y=0, max_y=1000, delta=500, of
client.move(x, y, _SWEEEP_HEIGHT) # move camera
take_photo(img_path)
client.shutdown()
- return pts # location应该写入文件 img/location
+ # write to img/location
+ with open(path.join(location_path, "location.txt"), 'w') as f:
+ for postion in pts:
+ f.write('{} {} {}\n'.format(postion[0], postion[1], _SWEEEP_HEIGHT))
+ return None
def take_photo(img_path: Path):
@@ -124,6 +129,13 @@ if __name__ == '__main__':
default="../img",
help='Mode for FarmBot, 1 for simple move with an assigned detination, 2 for scaning'
)
+ parser.add_argument(
+ '-loc',
+ '--locations',
+ type=Path,
+ default='../img/locations/',
+ help='the path to txt files contains locations from encoders corresponds to each photo'
+ )
parser.add_argument('-v', '--verbose', action='store_true', help='Verbose mode')
arguments = parser.parse_args()
@@ -138,8 +150,7 @@ if __name__ == '__main__':
simple_move(destination_x, destination_y, destination_z, photo)
Logger.info(f'time cost {time()-simple_move_start}')
elif arguments.mode == 2:
- simple_move(1000,0, -200)
- #scan(flag=False)
+ scan(arguments.photo, arguments.locations, flag=False)
else:
Logger.error('Wrong mode number {arguments.mode}')