I'm using a model for detecting objects on my Raspberry Pi, using python.
This is the python code:
import numpy as np
import cv2
import os,time
import tensorflow as tf
from object_detection.utils import label_map_util
from object_detection.utils import visualization_utils as vis_utils
# Init camera
cap = cv2.VideoC
apture(0)
cap.set(3,640) # set Width
cap.set(4,480) # set Height
# Init tf model
MODEL_NAME = 'ssdlite_mobilenet_v2_coco' #fast
PATH_TO_CKPT = MODEL_NAME + '/frozen_inference_graph.pb'
PATH_TO_LABELS = os.path.join('data', 'mscoco_label_map.pbtxt')
NUM_CLASSES = 90
IMAGE_SIZE = (12, 8)
fileAlreadyExists = os.path.isfile(PATH_TO_CKPT)
if not fileAlreadyExists:
print('Model does not exsist !')
exit
# LOAD GRAPH
print('Loading...')
detection_graph = tf.Graph()
with detection_graph.as_default():
od_graph_def = tf.compat.v1.GraphDef()
with tf.io.gfile.GFile(PATH_TO_CKPT, 'rb') as fid:
serialized_graph = fid.read()
od_graph_def.ParseFromString(serialized_graph)
tf.import_graph_de
f(od_graph_def, name='')
label_map = label_map_util.load_labelmap(PATH_TO_LABELS)
categories = label_map_util.convert_label_map_to_categories(label_map, max_num_classes=NUM_CLASSES,
use_display_name=True)
category_index = label_map_util.create_category_i
ndex(categories)
print('Finish Load Graph..')
# Main
t_start = time.time()
fps = 0
with detection_graph.as_default():
with tf.compat.v1.Session(graph=detection_graph) as sess:
while True:
ret, frame = cap.read()
# frame
= cv2.flip(frame,
-
1) # Flip camera vertically
# frame = cv2.resize(frame,(320,240))
##############
image_np_expanded = np.expand_dims(frame, axis=0)
image_tensor = detection_graph.get_tensor_by_name('image
_tensor:0')
detection_boxes = detection_graph.get_tensor_by_name('detection_boxes:0')
detection_scores = detection_graph.get_tensor_by_name('detection_scores:0')
detection_classes = detection_graph.get_tensor_by_name(
'detection_classes:0')
num_detections = detection_graph.get_tensor_by_name('num_detections:0')
print('Running detection..')
(boxes, scores, classes, num) = sess.run(
[detection_boxes, dete
ction_scores, detection_classes, num_detections],
feed_dict={image_tensor: image_np_expanded})
print('Done. Visualizing..')
vis_utils.visualize_boxes_and_labels_on_image_array(
frame,
np.squeeze(boxes),
np.squeeze(classes).astype(np.int32),
np.squeeze(scores),
category_index,
use_normalized_coordinates=True,
line_thickness=8)
##############
fps = fps + 1
mfps = fps / (time.time()
-
t_start)
cv2.putText(frame, "FPS " + str(int(mfps)), (10,10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0,0,255), 2)
cv2.imshow('frame', frame)
k = cv2.waitKey(30) & 0xff
if k == 27: # press 'ESC' to quit
break
cap.release()
cv2.destroyAllWindows()
There is an error that occurs that says: Traceback (most recent call last): File "/home/raspberrypi/Desktop/project/objectrec.py", line 31, in serialized_graph = fid.read() File "/home/raspberrypi/.local/lib/python3.10/site-packages/tensorflow/python/lib/io/file_io.py", line 116, in read self._preread_check() File "/home/raspberrypi/.local/lib/python3.10/site-packages/tensorflow/python/lib/io/file_io.py", line 77, in _preread_check self._read_buf = _pywrap_file_io.BufferedInputStream( tensorflow.python.framework.errors_impl.FailedPreconditionError: ssdlite_mobilenet_v2_coco/frozen_inference_graph.pb; Not a director
I don't know where the problem is, i was expecting that once I press run, the camera will work and detect objects around the room i'm in.
