Pay in installments of $17705.00 with
,
and
Shipping Estimate
USA
- USA
- CAN
- USA
- CAN
Ships within 48 hours · Estimated delivery Aug 23 - Aug 28
Promo Codes Available:
For Your Every Summer RSVP, with Code: SUMMER15
Description
ACTi Q113 2MP Indoor L-Shape Covert Pinhole PoE Network Camera SystemThe ACTi Q113 2MP Indoor L Shape Covert Pinhole PoE Network Camera System includes a pinhole camera and main unit. The camera utilizes a 1 2. 8" progressive scan CMOS image sensor and 3. 7mm fixed lens to capture images up to 1920 x 1080 at 30 fps. It offers Superior Low Light Sensitivity basic WDR of 75 dB for capturing clear images in low light environments. The camera features a 39' cable for connection to the main unit, which can be placed out of
The ACTi Q113 2MP Indoor L-Shape Covert Pinhole PoE Network Camera System includes a pinhole camera and main unit. The camera utilizes a 1/2.8" progressive scan CMOS image sensor and 3.7mm fixed lens to capture images up to 1920 x 1080 at 30 fps. It offers Superior Low Light Sensitivity basic WDR of 75 dB for capturing clear images in low-light environments. The camera features a 39' cable for connection to the main unit, which can be placed out of public view.
The main unit houses connections for the camera, network, power, digital input/output, and RS232 data port. It supports two-way audio and features a microSDHC / SDXC memory card slot (card not included) for local storage of recordings. This network camera system is suitable for discreet indoor video surveillance. The camera unit can be ceiling or wall mounted using flush, surface, or tilted mounts (included) or the height strip mount (available separately). The main unit can be directly mounted on the included mounting rail or on a DIN rail (available separately) for flexible installations.
- 1/2.8" progressive scan CMOS image sensor
- 3.7 mm, f/2.5 fixed lens with horizontal viewing angle of 84.5�
- Records up to 1920 x 1080 images at 30 fps
- Superior Low Light Sensitivity and Basic WDR (75 dB)
- microSDHC / SDXC memory card slot (card not included)
- LED status indicators
- EN50155 compliant vibration-proof casing
In the Box
ACTi Q113 2MP Indoor L-Shape Covert Pinhole PoE Network Camera System
- Mounting Rail
- Power Terminal Block
- Digital In/Out Terminal Block
- Audio In/Out Terminal Block
- RS-232 Terminal Block
- Surface Mount
- Flush Mount
- Tilted Mount
- Mounting Hardware
- 2 x Drill Template
- Limited 3-Year Warranty
| Device | |
|---|---|
| Device Type | Indoor L-shape pinhole covert camera |
| Image Sensor | 1/2.8" progressive scan CMOS |
| Effective Pixels (H x V) | 1944 x 1224 (2.38 MP) |
| Low Light Sensitivity | Superior |
| Minimum Illumination | Color: 0.1 lux at f/2.5 (30 IRE, 2400�K) |
| Electronic Shutter | 1/5 to 1/32,000 sec (manual & auto mode) |
| Horizontal Resolution | 1100 TVL |
| S/N Ratio | 52 dB |
| Lens | |
|---|---|
| Focal Length | 3.7 mm |
| Aperture | f/2.5 |
| Iris | Fixed |
| Focus | Fixed |
| Horizontal Viewing Angle | 84.5� |
| Video | |
|---|---|
| Compression | H.264 (Baseline / Main / High profile), MJPEG |
| Maximum Frame Rate vs. Resolution | 30 fps at 1920 x 1080, 1280 x 720, 800 x 600, 640 x 480 15 fps at 320 x 240 |
| Multi-Streaming | Simultaneous dual streams based on two configurations |
| Bit Rate | 28 kb/s to 6 Mb/s (per stream) |
| Bit Rate Mode | Constant, variable |
| Image Enhancement | Basic WDR: 75 dB White Balance: Automatic, hold, and manual Brightness Contrast Sharpness (auto) Auto Gain Control 2D+3D Digital Noise Reduction Flickerless |
| Privacy Masking | 4 configurable regions |
| Text Overlay | User defined text on video |
| Image Orientation | Image flip and mirror |
| Audio | |
|---|---|
| Compression | 8 kHz, mono, PCM, 16-bit encoding; G.711 |
| Audio In | Mic-in and line-in, terminal block |
| Audio Out | Line-out, terminal block |
| Network | |
|---|---|
| Protocol | TCP, UDP, HTTP, HTTPs, DHCP, PPPoE, RTP, RTSP, IPv4, IPv6, DNS, DDNS, NTP, ICMP, ARP, IGMP, SMTP, FTP, UPnP, SNMP, Bonjour |
| Ethernet Port | 1 x RJ45 (10/100 Base-T) connector |
| Security | IP address filtering HTTPs encryption Password protected user levels Anonymous login IEEE802.1X network access control |
| Alarm | |
|---|---|
| Alarm Trigger | Video motion detection (3 regions) External device through digital input Sound detection |
| Alarm Response | Notify control center Change camera settings Command other devices E-mail notification with snapshots Save video or snapshot to local storage Upload video or snapshot to FTP Activate external device through digital output |
| Interface | |
|---|---|
| Digital Input | 1 x Terminal block |
| Digital Output | 1 x Terminal block |
| Serial Port | 1 x RS-232 |
| Local Storage | microSDHC / SDXC memory card slot (card not included) |
| Integration | |
|---|---|
| Unified Solution | Fully compatible with ACTi software |
| ISV Integration | ONVIF compliant Software Development Kit (SDK) available |
| GPS | Manual setting |
| Firmware Access Browser | Microsoft Internet Explorer 8.0 or newer (full functionality) Safari with QuickTime installed, and other browsers with VLC installed (partial functionality) |
| General | |
|---|---|
| Power Source | PoE Class 2 (IEEE802.3af) 12 VDC (adapter not included) |
| Power Consumption | PoE: 4.32 W 12 VDC: 3.6 W |
| Mount Type | Flush, surface, and tilted mount (included) Height strip mount (available separately) |
| Temperature | Starting: -4 to 122�F (-20 to 50�C) Operating: -22 to 140�F (-30 to 60�C) |
| Operating Humidity | 10 to 85% RH |
| Approvals | CE (EN 55022 Class B, EN 55024) FCC (Part15 Subpart B Class B) UL (for optional PoE injector and power adapter |
| Environmental Casing | Vibration proof (EN50155) |
| Dimensions (L x W x H) | 3.95 x 2.95 x 1.00" (100.33 x 75.00 x 25.50 mm) |
| Weight | 1.120 lb (0.508 kg) |
Shipping Notes
- Free Standard Shipping on $100+ Orders to the USA.
- Except Preorder products are shipped in 48 hours.
- Delivery to the USA:
- Standard Shipping : 3-10 business days
- If time is of the essence, please consider selecting expedited delivery for faster service.
Exchange/Return Notes
- We offer a 30-day return/exchange service after receiving.
- Final sale items are not eligible for returns or exchanges.
- To process your return/exchange, please contact us at [email protected]
- Please click here for more details>>> Return & Exchange Policy
4.1 ★★★★★
Based on 11 reviews
Sort
Product Reviews
★★★★★ 5
Excellent book on ML
Format: Paperback
This is a great book on machine learning. Topics covered are extensive - from beginner level to advanced topics including math behind different algorithms. However, not "all" algorithms are covered. Please go through the table of contents.
The first part - 11 chapters - covers machine learning concepts and second part covers advanced topics with Pytorch. There are lots of excellent code and they work!!
The quality of the book I received is excellent. I have gone through all 742 pages, and it has held up very well!!
I used Jupyter notebook to run all examples. I created a new notebook and copied and pasted the code and ran them. This approach worked very well for me. At the same time, I could experiment with my take on the code snippets and definitely added to my knowledge.
Only issue I have is on the second part of the book discussing PyTorch: (1) Some packages are a bit older version: e.g., transformer 4.9.1 whereas current version is 4.48+. It took some tweaking/recoding to get the examples working. (2) There is not much discussion on why certain architecture was chosen - e.g., number of layers, is there a rule of thumb on how to improve performance by changing these parameters? Even with CUDA the code run for a long time. Therefore, experimenting with different values of parameters become too time consuming. (3) On the same note, if I can achieve test accuracy of 90%+ using logistic regression and almost the same (perhaps one or two percent better with PyTorch with IMDB movie review dataset and that two much faster why should I use PyTorch for this dataset? Obviously, PyTorch is for certain types of problems. Discussions can be included by not adding to the exhaustive (and apt) contents.
Personally I was disappointed by lack of any example on time series.
Must have for ML practitioner as a reference and guide.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 20, 2024
★★★★★ 5
Excellent Textbook for Hands-On Learning of ML
Format: Kindle
This textbook is for the serious life-long learners of machine learning. There are at least two ways to ‘consume’ this book.
For the expert in ML, this is a textbook to study as a clear comprehensive ML overview and then to dive into sections of interest or ignorance. The concepts are grounded in code examples and are well cited (with links) to sources. Further, this textbook is appropriate if you are TensorFlow-centric and want to broaden into cutting-edge ML models/tools coded in PyTorch.
For a new learner to ML, this is a textbook to DO (not just READ) with hands-on and brain-engaged. If you realize that ML is a key life-long skill for your career, consider this textbook as part of a daily learning habit (10-30 min).
From personal experience, my advice to the new learner is as follows… First, clone the GitHub repository, setup your Python environment, and study the textbook, while working through the notebooks. Go on tangents and break the code. Do this methodically as part of your daily learning habit, but do not hesitate to jump ahead several chapters to prepare for tomorrow’s meeting. There is enough excellent material here for a full year of ML adventures.
I did a similar strategy with Raschka’s first textbook. About four years ago, I had finished Andrew Ng’s Deep Learning Specialization as a student in his first cohort. I knew the concepts well but could not do the actual application coding. I was surprised how my Python coding improved by following Raschka’s clean and elegant style. And Raschka’s code examples were meaty enough to be springboards into working applications.
Several textbook editions later, what is different about this new edition?
First, it moves you through scikit-Learn (a firm foundation) to PyTorch, instead of TensorFlow. PyTorch is a better stepping-stone, both conceptually and practically. With PyTorch, you will go further with less energy, while being able to convert your efforts into TensorFlow as needed. In addition, most of the cutting-edge ML/AI/DL research is in PyTorch. It is nice to read a recent arXiv paper, clone their repository, click on the Colab tutorial, and replicate their experiments, along with picking up a ton of new coding tricks & tips. I am excited to work through these PyTorch sections to hone my skills.
Second, there is a clear recognition of model tracking and tuning practices. This is often a gap in other ML textbooks and courses. Once you progress beyond the simple demo examples in a lecture, you realize that the real work is experiments, more experiments, and still more experiments, so that you must understand what the model architecture and hyperparameters are doing to your dataset. There is good coverage of scikit-Learn pipeline, grid search, model performance, and the like.
Third, ML/AI/DL practice is rapidly evolving. Every week new ML packages/services become available that could save much grief on your current project. What is refreshing about Raschka’s textbook series is that he constantly adding cutting-edge topics because he likes to stay current and to help us stay current. Hence, this edition contains recent ML treats as: transformers, self-supervised learning, autoencoders-to-GAN, graph neural networks, DBSCAN, t-SNE (with brief mention of UMAP), and PyTorch-Lightning.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on February 26, 2022
★★★★★ 4
Just learning it
Format: Paperback
Nice learning book just have to finish it
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 10, 2025
★★★★★ 5
Very useful book
Format: Paperback
I use it for the machine learning class I teach.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 3, 2026
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 4, 2026