Tensorflow Object Detection API ptax Error with ptax

[NiksanJP]

So I have this code

`import numpy as np
import os
import six.moves.urllib as urllib
import sys
import tarfile
import tensorflow as tf
import zipfile
from collections import defaultdict
from io import StringIO
from matplotlib import pyplot as plt
from PIL import Image
import cv2
cap = cv2.VideoCapture(0)
sys.path.append("..")

from object_detection.utils import label_map_util
from object_detection.utils import visualization_utils as vis_util

model = 'rfcn_resnet101_coco_2018_01_28'

MODEL_NAME = model
MODEL_FILE = 'D:/Python/' + model

PATH_TO_CKPT = 'D:/Python/' + model + '/frozen_inference_graph.pb'

PATH_TO_LABELS = 'D:/Python/mscoco_label_map.pbtxt'

NUM_CLASSES = 90

detection_graph = tf.Graph()
with detection_graph.as_default():
od_graph_def = tf.GraphDef()
with tf.gfile.GFile(PATH_TO_CKPT, 'rb') as fid:
serialized_graph = fid.read()
od_graph_def.ParseFromString(serialized_graph)
tf.import_graph_def(od_graph_def, name='')

with detection_graph.as_default():
od_graph_def = tf.GraphDef()
with tf.gfile.GFile(PATH_TO_CKPT, 'rb') as fid:
serialized_graph = fid.read()
od_graph_def.ParseFromString(serialized_graph)
tf.import_graph_def(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_index(categories)

with detection_graph.as_default():
with tf.Session(graph=detection_graph) as sess:
while True:
ret, image_np = cap.read()
# Expand dimensions since the model expects images to have shape: [1, None, None, 3]
image_np_expanded = np.expand_dims(image_np, axis=0)
image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')
# Each box represents a part of the image where a particular object was detected.
boxes = detection_graph.get_tensor_by_name('detection_boxes:0')
# Each score represent how level of confidence for each of the objects.
# Score is shown on the result image, together with the class label.
scores = detection_graph.get_tensor_by_name('detection_scores:0')
classes = detection_graph.get_tensor_by_name('detection_classes:0')
num_detections = detection_graph.get_tensor_by_name('num_detections:0')
# Actual detection.
(boxes, scores, classes, num_detections) = sess.run(
[boxes, scores, classes, num_detections],
feed_dict={image_tensor: image_np_expanded})
# Visualization of the results of a detection.
vis_util.visualize_boxes_and_labels_on_image_array(
image_np,
np.squeeze(boxes),
np.squeeze(classes).astype(np.int32),
np.squeeze(scores),
category_index,
use_normalized_coordinates=True,
line_thickness=8)
cv2.imshow('object detection', cv2.resize(image_np, (800,600)))
`

I have entered all the folder locations and the name correctly. I
get CUDNN_STATUS_INTERNAL_ERROR OR
heaps of
2019-06-28 00:04:13.171528: W tensorflow/stream_executor/cuda/redzone_allocator.cc:294] Internal: Invoking ptxas not supported on Windows Relying on driver to perform ptx compilation 2019-06-28 00:04:13.198421: W tensorflow/stream_executor/cuda/redzone_allocator.cc:294] Internal: Invoking ptxas not supported on Windows Relying on driver to perform ptx compilation 2019-06-28 00:04:13.207294: W tensorflow/stream_executor/cuda/redzone_allocator.cc:294] Internal: Invoking ptxas not supported on Windows Relying on driver to perform ptx compilation

OS: Windows 10
Tensorflow: 2.0.0b and 1.14
CUDA: 10

Need help!

[tensorflowbutler]

Thank you for your post. We noticed you have not filled out the following field in the issue template. Could you update them if they are relevant in your case, or leave them as N/A? Thanks.
What is the top-level directory of the model you are using
Have I written custom code
OS Platform and Distribution
TensorFlow installed from
TensorFlow version
Bazel version
CUDA/cuDNN version
GPU model and memory
Exact command to reproduce

[Acejoy]

yes i too have the same the same issue

System information
What is the top-level directory of the model you are using:
\models\research\object_detection\

Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
NO, trying to use model_main.py

OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
Windows 10

TensorFlow installed from (source or binary):
installed using pip(pip install tensorflow-gpu)

TensorFlow version (use command below):
v2.0.0

Bazel version (if compiling from source):
N/A

CUDA/cuDNN version:
CUDA Version 10.0.130
cuDNN: 7.6.4

GPU model and memory:
GeForce GTX 1050 4 GB dedicated, 3.9 GB shared

Exact command to reproduce:
runt the object_detection_tutorial.ipynb file

Describe the problem
and it got stuck at the loop where the image results were meant to be shown i.e.:-

for image_path in TEST_IMAGE_PATHS: show_inference(detection_model, image_path)

.
It stayed here until the jupyter notebook dispalyed a message saying kernel has died.
When tried to run it in anaconda prompt ,the following was displayed at the end after which the no images were shown and the process ended.

W tensorflow/stream_executor/cuda/redzone_allocator.cc:312] Internal: Invoking ptxas not supported on Windows
Relying on driver to perform ptx compilation. This message will be only logged once.

Please look into this matter.

[NiksanJP]

yes i too have the same the same issue

System information
What is the top-level directory of the model you are using:
\models\research\object_detection\

Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
NO, trying to use model_main.py

OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
Windows 10

TensorFlow installed from (source or binary):
installed using pip(pip install tensorflow-gpu)

TensorFlow version (use command below):
v2.0.0

Bazel version (if compiling from source):
N/A

CUDA/cuDNN version:
CUDA Version 10.0.130
cuDNN: 7.6.4

GPU model and memory:
GeForce GTX 1050 4 GB dedicated, 3.9 GB shared

Exact command to reproduce:
runt the object_detection_tutorial.ipynb file

Describe the problem
and it got stuck at the loop where the image results were meant to be shown i.e.:-

for image_path in TEST_IMAGE_PATHS: show_inference(detection_model, image_path)

.
It stayed here until the jupyter notebook dispalyed a message saying kernel has died.
When tried to run it in anaconda prompt ,the following was displayed at the end after which the no images were shown and the process ended.

W tensorflow/stream_executor/cuda/redzone_allocator.cc:312] Internal: Invoking ptxas not supported on Windows
Relying on driver to perform ptx compilation. This message will be only logged once.

Please look into this matter.

I have looked into the matter and I decided to re-install everything. It worked

[Acejoy]

yes i too have the same the same issue
System information
What is the top-level directory of the model you are using:
\models\research\object_detection
Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
NO, trying to use model_main.py
OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
Windows 10
TensorFlow installed from (source or binary):
installed using pip(pip install tensorflow-gpu)
TensorFlow version (use command below):
v2.0.0
Bazel version (if compiling from source):
N/A
CUDA/cuDNN version:
CUDA Version 10.0.130
cuDNN: 7.6.4
GPU model and memory:
GeForce GTX 1050 4 GB dedicated, 3.9 GB shared
Exact command to reproduce:
runt the object_detection_tutorial.ipynb file
Describe the problem
and it got stuck at the loop where the image results were meant to be shown i.e.:-
for image_path in TEST_IMAGE_PATHS: show_inference(detection_model, image_path)
.
It stayed here until the jupyter notebook dispalyed a message saying kernel has died.
When tried to run it in anaconda prompt ,the following was displayed at the end after which the no images were shown and the process ended.

W tensorflow/stream_executor/cuda/redzone_allocator.cc:312] Internal: Invoking ptxas not supported on Windows
Relying on driver to perform ptx compilation. This message will be only logged once.

Please look into this matter.

I have looked into the matter and I decided to re-install everything. It worked

okay so reinstall as in only the tensorflow gpu or entire cuda along with cudnn and tensorflow-gpu ?
Can you please tell the steps you took to resolve this?
I will be really grateful.

Thanks in advance

[Acejoy]

hey can you please oshare the steps you took to resolve the problem? I will be really grateful

…

On Mon, Oct 28, 2019 at 8:33 AM Nikheil Malakar ***@***.***> wrote: Closed #7113 <#7113>. — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#7113?email_source=notifications&email_token=AIXRJJ5XXIOC7KH3OTLYCW3QQZJB7A5CNFSM4H347IWKYY3PNVWWK3TUL52HS4DFWZEXG43VMVCXMZLOORHG65DJMZUWGYLUNFXW5KTDN5WW2ZLOORPWSZGOUO7DCDA#event-2747150604>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AIXRJJ376P5UTZ5XJZE46Z3QQZJB7ANCNFSM4H347IWA> .

[DzakirinMD]

Hello i've encountered the same problem and yes the problem can be resolve by reinstalling everything

@Acejoy just reinstall the conda environment and just rerun back the object_detection_tutorial.ipynb file

[hemantghuge]

Issue not solved

[philipsolomonsee]

Hi everyone,
I have tried everything : reinstalled tensorflow-gpu 2.1,2.0,1.15 , including installing cuda toolkit 10.0,10.1 according to their respective cudnn version, THE ERROR still exist.

The only to solve this is DOWNGRADE to tensorflow-gpu 1.14.. It will works

[michalzielinski913]

The only to solve this is DOWNGRADE to tensorflow-gpu 1.14.. It will works

It worked for me too, ty.