Tensorflow Object Detection in 5 Hours with Python | Full Course with 3 Projects

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Recommends coding_world · 2023-03 · Stack Overflow · on “Object Detection using Tensorflow and Python”

I am following a youtube video which shows how to use tensorflow in Jupyter notebook for obstacle detection. The video link is: [this video] GitHub files: [LINK] I have run into an issue at 2:12 in the video. I have collected. my images and have labelled them accordingly, I am now trying to create a .record file, however this is not being created upon execution of the following lines of code, furthermore no error is given and I am running it on mac os. import os CUSTOM_MODEL_NAME = 'my_ssd_mobnet' PRETRAINED_MODEL_NAME = 'ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8' PRETRAINED_MODEL_URL = ' [LINK] ' TF_RECORD_SCRIPT_NAME = 'generate_tfrecord.py' LABEL_MAP_NAME = 'label_map.pbtxt' paths = { 'WOR

Recommends Ali Abdullah · 2023-05 · Stack Overflow · on “tensorflow Object detection model not working with webcam”

I have trained object detection model using tensorflow 2.10.1 in python 3.9. I'm trying to use it in webcam but it gives me following error [LINK] This is the code I'm using. I followed this [this video] tutorial. import tensorflow as tf from object_detection.utils import label_map_util from object_detection.utils import visualization_utils as viz_utils from object_detection.builders import model_builder from object_detection.utils import config_util import cv2 import numpy as np from matplotlib import pyplot as plt # Load pipeline config and build a detection model configs = config_util.get_configs_from_pipeline_file(r"K:\new\training_demo\pre-trained-models\ssd_mobilenet_v2_fpnlite_320x320_coco

Cites J.Todd · 2021-06 · Stack Overflow · on “Is there any negative effect for using cropped images with the TFRecord format?”

I know I need the bounding box information. I'm asking if the image referenced by the bounding box needs to be any larger than the bounding box. I'm not sure you fully understood my question. I built a tool where I can walk through frames of a video, select rectangles containing just the object to classify, and export them as individual jpegs and creates an XML file alongside the image of that selection, like shown here: [this video] note the timestamp). The difference is that example exports the full image with the cropped XML coords, where as (1/2)

Cites piperdaniel1 · 2021-07 · Stack Overflow · on “Error "Numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject."”

I got this error file while following this tutorial: [this video] So far I have created a training dataset to feed into Tensorflow. I am using transfer learning on one of the pre-trained TensorFlow object recognition models. I get the error when I attempt to train the model with my new dataset. This is a picture of the full error message that shows up [LINK] . I attempted to solve the problem by trying the following: Reinstalling Numpy Installing Numpy 1.20.x Installing Numpy 1.18.x Reinstalling pycocotools When I installed Numpy 1.20.x the error went away and was replaced with a separate error: notimplementederror: cannot convert a symbolic Tensor (cond_2/strided:0) to a numpy array. This seemed

Cites J.Todd · 2021-07 · Stack Overflow · on “How can I convert the model I trained with Tensorflow (python) for use with TensorflowJS without involving IBM cloud (from the step I'm at now)?”

What I'm trying to do I'm trying to learn TensorFlow object recognition and as usual with new things, I scoured the web for tutorials. I don't want to involve any third party cloud service or web development framework, I want to learn to do it with just native JavaScript, Python, and the TensorFlow library. What I have so far So far, I've followed a TensorFlow object detection tutorial [LINK] (accompanied by a 5+ hour video [this video] ) to the point where I've trained a model in Tensorflow (python) and want to convert it to run in a browser via TensorflowJS. I've also tried other tutorials and haven't seemed to find one that explains how to do this without a third party cloud / tool and React.

Cites Apuroop_M · 2021-07 · Stack Overflow · on “IAE: Expected 'tf.Tensor(False, shape=(), dtype=bool)' to be true. Summarized data: b'maximum box coordinate value is larger than 1.100000”

I am following this tutorial, but with my own data: [this video] I ran into this error, I trained my data successfully but when trying to evaluate my data I am running into this error: tensorflow.python.framework.errors_impl.InvalidArgumentError: Expected 'tf.Tensor(False, shape=(), dtype=bool)' to be true. Summarized data: b'maximum box coordinate value is larger than 1.100000: '1.2443783 It was actually successful before, as I trained a model last night and could evaluate it, but I wanted to retrain it from scratch because it wasn't detecting very well. I recompressed my images into JPG and relabelled them(used LabelImg), deleted previous checkpoints, then tried again and this is what I'm getti

Cites Shella · 2021-08 · Stack Overflow · on “How do I install TensorFlow 2 & the object_detection module?”

Background I've been trying to follow the tutorial in this [this video] video. The goal is trying to install TensorFlow and TensorFlow's object_detection module. Goal How do I install it so that I can follow the rest of the tutorial? I only want to install the CPU version. Additional Information Errors that I ran into ERROR: Could not find a version that satisfies the requirement tensorflow==2.1.0 (from versions: None) ERROR: No matching distribution found for tensorflow ERROR: tensorflow.whl is not a supported wheel on this platform. ##Research## [LINK] Tensorflow installation error: not a supported wheel on this platform [LINK]

Cites CS_Student101 · 2021-08 · Stack Overflow · on “How to read, save and display images, encoded in csv format”

I'm working on a project for sign language detection. I needed more data, so I found it here: [LINK] However, I still don't quite understand how it all works. I found similar videos like this one [this video] but they don't work with csv. So I wonder if there is a way to somehow process these images. As for the label, I'm trying to figure that out too

Cites Aeronos · 2021-11 · Stack Overflow · on “illegal hardware instruction”

I'm trying to do this YouTube formation on TensorFlow : [this video] . At some step, I want to run the 'generate_tfrecord.py' with the following command : python TensorFlow/scripts/generate_tfrecord.py -x Tensorflow/workspace/images/train -l Tensorflow/workspace/annotations -o Tensorflow/workspace/annotations in my terminal and I have this answer : zsh: illegal hardware instruction python TensorFlow/scripts/generate_tfrecord.py -x -l -o and in Jupiter Notebook : 4348 Illegal instruction: 4 What can I do to avoid this and to just run the python file ? I'm working on Mac OS Monterey on a M1 Macbook. Thanks for your help.

Cites Mehtab Singh · 2021-12 · Stack Overflow · on “Trying to add an alert to detection model "ssd_mobilenet_v2", throws an error”

Using "ssd_mobilenet_v2_fpn_keras" i am trying to add an alert system The detection model is loaded in to the below function def detect_fn(image): image, shapes = detection_model.preprocess(image) prediction_dict = detection_model.predict(image, shapes) detections = detection_model.postprocess(prediction_dict, shapes) return detections The image is converted to a tensor input_tensor = tf.convert_to_tensor(np.expand_dims(image_np, 0), dtype=tf.float32) The the tensor is fead to the detection model detections = detect_fn(input_tensor) The output of the detection model is a dictionary, with the following keys: dict_keys(['detection_boxes', 'detection_scores', 'detection_classes', 'raw_detection