Roboflow

...团队 / 企业） 1. Roboflow（计算机视觉...

... de déploiement spécifique. RF-DETR (de Roboflow) – Précision maximale Le modèle en... de contrôle pré-entraîné sur COCO. Roboflow propose également une interface utilisateur...

... similar model such as RF-DETR (Roboflow Detection Transformer). Using these base...

... YOLO11 مع ترخيص تجاري. * تدعم Roboflow وSenseCraft AI لتطوير ونشر نماذج...

Pidele a claude que te de un trozo de codigo que use un modelo yolo preentrenado para dibujar rectangulos sobre caras y matriculas Te vas a roboflow o a ultralytics mismo que tendran un modelo que tirara bastante bien y lo descargas Easyyy

... sehr nützlich war: https://blog.roboflow.com/depth-estimation-models/ Und hier ein...

..., @​manavm1990, @​langy, @​roboflow, @​syntaxfm, @​getsentry, @...

... 제조 검사 AI Roboflow 제조 검사/데...

...醫）、Rittal（威圖）、RLWRLD、Roboflow、Runway、Ryoyo Ryosan、Samsung（三...

... verticals that are underrepresented on Roboflow Universe — construction, medical devices, HVAC...

... verticals that are underrepresented on Roboflow Universe — construction, medical devices, HVAC...

https://playground.roboflow.com/evals

... a easier alternative to the RoboFlow labeling → Training → Convert method I ...

... CVAT, but ended up with Roboflow due to its easy-to-use UI...

... CVAT, but ended up with Roboflow due to its easy-to-use UI...

.... For our approach, we used Roboflow for our image annotation and...

.... I trained the models with Roboflow, annotating roughy 1,200 image... (Roboflow has a Auto-Annotate which is ...

..., though: both detectors trained on Roboflow datasets the team labeled by ....js, Prisma, BullMQ, Cloudflare Tunnel, Roboflow. People I’d like to acknowledge ...

submitted by /u/TeslaLegacy to r/CerebroDigital [link] [comments]

https://preview.redd.it/3t03ix6i42ah1.png?width=1850&format=png&auto=webp&s=527292a211de4624ff03988cae82b0027e98764e Got an email saying I used all my credits. Roboflow dashboard says I have used 0/15 and then wont tell me the usage. Anyone else have this issue? Customer service email is not responding. UPDATE: Seeing a number of posts in the forum. They need to address this ASAP as it makes it unusable for many users! submitted by /u/SevereAttitude2648 to r/roboflow [link] [comments]

submitted by /u/julesbutgreener to r/roboflow [link] [comments]

this post is not strictly spectacles, but more about Roboflow and deploying a trained model to Lens Studio to then use in Spectacles. I believe Roboflow has recently had a change in their UII and have not yet documented their changes. I am trying to deploy to Lens Studio through the 3rd part deployment button, but no matter what I do, it will not let me export to Lens studio. I only see the Open MV option. I have tried this about 6 times already and thoroughly read the documentation to make sure i am doing it right, spoken to technical help, and I am so confused as to why this is not working. Just to be completely clear, here are my specifications before training the mode - I am just training a test model for now, but I want to do multi object detection for custom models, so i cannot use templates for this. Any help? Roboflow 3.0 (Fast) ~68 images https://preview.redd.it/f098knzu21ah1.png?width=1436&format=png&auto=webp&s=8666e43e7f71b787ceb96f9830c1f4e52cdca98b https://preview.redd.it/71cn8a0v21ah1.png?width=2768&format=png&auto=webp&s=110fe8390075c154a02e276fdd6f947b99d791d6 https://preview.redd.it/trc41abv21ah1.png?width=2176&format=png&auto=webp&s=47b1b31cc025201dc4fec50e8ce23abe4134280f 62 train / 4 valid / 2 test 640x640 (Stretch to) 2 preprocessing steps 3 augmentations 300 epochs MS COON submitted by /u/julesbutgreener to r/Spectacles [link] [comments]

submitted by /u/WearyDirection4803 to r/roboflow [link] [comments]

submitted by /u/WearyDirection4803 to r/roboflow [link] [comments]

I found a Universe Dataset that works well on my test images so I downloaded the Yolov8 dataset and trained the yolov8n.pt model with the additional weights then used the best.pt file. However, yolov8 doesn't find any objects on the same images. I confident I'm using the correct weights file because it has the new classes. I'm asking to better understand the discrepancy. Edit: https://universe.roboflow.com/alexeyvoronin/railroad-cars-pyjpo submitted by /u/stevemac00 to r/computervision [link] [comments]

Has anyone else had this issue? My keypoint skeleton has 3 keypoints. When analyzing my json file of annotations for coco model for keypoint detection, im finding a lot of these are having their num_keypoints as non multiples of 3. I've gone through my dataset and redone my annotations so the keypoints have enough space, and nothing has been deleted or hidden. I'm not sure whats going on and this is really frustrating. submitted by /u/5_1_2021 to r/computervision [link] [comments]

submitted by /u/Critical-Self7283 to r/deeplearning [link] [comments]

I have been working from past 2 years, I am just obsessed with dataset management and a quality annotation framework that supports collaboration annotation, sure thing no body does annotation by hand today and better pretrained models are available but if you are optimizing for the cost and hardware and accuray, you may need to inspect you dataset or train model etc For eg yolo26n is only 5MBs but to make it run accurately for you use case you would still need controol on your dataset, and sometimes there is more than just object detection in a frame we support all kind of annotations in the same editor. submitted by /u/Critical-Self7283 to r/computervision [link] [comments]

Roboflow is hiring for a Machine Learning Research Engineer. Dive into novel computer‑vision research, publish to top conferences & ship production‑scale ML. Tech: Python, PyTorch, CV, Deep Learning.\ Salary: $168k‑$255k. Apply: https://aihackerjobs.com/company/roboflow/job/21965 submitted by /u/varworld to r/DataScienceJobs [link] [comments]

Didn’t like paying for roboflow or any of the free CV tools so built a free, local alternative for anyone who doesn't want to deal with cloud limits or pricing tiers. Open sourced it this week. The idea was one app that handles the full loop from annotation through to training, without needing to export files. Features: - Manual annotation + auto-annotation (YOLO, RF-DETR, GroundingDINO, SAM 1/2/3) - Video frame extraction - Dataset merging, class extraction, format conversion - YAML auto-generation - Augmentation - No-code model training (YOLO + RF-DETR) - Fast sort/filter for reviewing large datasets It’s not fully polished as it started as something to scratch my own itch, but I’d love to know if others find it useful, or what might be missing from your workflows. Lmk what you think: https://github.com/Dan04ggg/VisOS submitted by /u/Low-Inspection5343 to r/computervision [link] [comments]

im working on a keypoint detection project. i annotated a few images allready and decided to train a model in roboflow to check if it works. is there a way that i can use that model to help me annotate the rest of the images? submitted by /u/bini_the_boomer to r/roboflow [link] [comments]

TL;DR: Object detection on ESP32-P4, 25% faster than the current best option, now merged into Espressif's official esp-dl. One notebook to train on your own dataset and deploy. Technical deep-dive below. I've been working on deploying YOLO26n (the latest Ultralytics architecture) on the ESP32-P4, and after months of quantization pain, the implementation just got merged into Espressif's official esp-dl repository as the reference YOLO26n example for both P4 and S3. If you just want to deploy a custom model: You can now train YOLO26n on any Roboflow dataset any image size, any number of classes and export it to both ESP32-P4 and ESP32-S3 with a single notebook. No C++ changes needed, the firmware auto-detects everything at runtime. Jump to the one-click pipeline section below. The numbers: 2,062ms inference at 512×512, 36.5% mAP on COCO 25% faster than the official YOLOv11n baseline at equivalent accuracy. Why was this hard? If you've ever tried quantizing a model for the P4, you know the drill: everything needs to run in INT8 on the PIE SIMD extensions or you pay a massive latency penalty. Standard YOLO architectures handle this reasonably well because their detection heads use Distribution Focal Loss (DFL with RegMax=16), which spreads quantization noise across multiple bins. YOLO26n doesn't have that luxury. It uses RegMax=1 direct regression with a single value per coordinate. There's no DFL buffer. INT8 activations in the detection head completely destroyed bounding box regression. The model could classify objects fine, but the boxes were garbage. The INT16 Swish problem So I needed INT16 precision in the sensitive layers. The catch: ESP-DL's native INT16 Swish falls back to a dequantize → float32 → requantize path, adding ~660ms per layer. Total inference shot past 5 seconds. The only fast path is ESP-DL's hardware-accelerated LUT interpolation a compact 4KB table that the hardware interpolates between at runtime. But here's the real problem: esp-ppq (the quantization tool) didn't know about this LUT behavior. Python used standard float32 Swish during validation, while the chip computed stepped integer interpolation. So your Python accuracy numbers were lying to you, and QAT couldn't learn to compensate for the actual hardware behavior. The solution: esp_ppq_lut I built a library called esp_ppq_lut that creates a bit-exact emulation of ESP-DL's LUT interpolation inside Python. Pure integer arithmetic, matching the chip's truncation behavior exactly (C truncates toward zero, Python floors toward negative infinity this matters). Validated it with a 4-test firmware protocol on real P4 hardware: 0 errors across 451,584 output values. Without the library, Python would predict 399,044 wrong values (88.4% of outputs) compared to what actually runs on-chip. During this work I also found an off-by-one bug in esp-ppq's LUT exporter the table had 2,048 entries instead of the required 2,049 (N+1 boundaries for N segments), causing out-of-bounds memory reads for high positive inputs. Fix was adopted by the maintainers. What's now in esp-dl models/yolo26 Generic C++ component that auto-detects input shape, output dtype, and class count from the .espdl header at runtime examples/yolo26_detect Production firmware for both stock COCO and custom models examples/tutorial/how_to_quantize_model/quantize_yolo26 End-to-end Jupyter notebooks for the full pipeline The "one-click" custom model pipeline This is probably the most useful part for this community: you can now train and deploy a custom object detection model to P4 or S3 without touching the C++ code. Paste your Roboflow API key, pick a dataset (any number of classes), choose your resolution (160–640px), and the notebook handles fine-tuning, quantization (PTQ → TQT → INT16 LUT fusion), and .espdl export. The firmware auto-detects everything at runtime. I tested it with a 28-class Lego Brick dataset from Roboflow works out of the box. Links Merged PR #286 esp_ppq_lut library One-click quantization notebook Full technical writeup My GitHub LinkedIn I regularly post updates on my embedded ML projects, follow along if you're into this kind of stuff. Happy to answer questions about the quantization pipeline, the LUT emulation, or anything P4-related. yolo26n on esp32 submitted by /u/Efficient_Royal5828 to r/esp32 [link] [comments]

I have a small computer vision project and I thought I would try out Roboflow. Their assisted labeling tool is really great, but from my short time using it, I have encountered a lot of flakiness. Often, a click fails to register in the labeling tool and the interface says something about SAM not being available at the moment and please try again later. Sometimes I delete a label and the delete doesn't register until I refresh the page. Ditto for deleting a dataset. I tried to train a model, and it got stuck on "zipping files." The same thing happened when I tried to download my dataset. Anyone else have experience with Roboflow? I found other users with similar issues dating back to 2022 https://discuss.roboflow.com/t/can-not-export-dataset/250/18 It seems the reliability is not what it should be for a paid tool. How often is Roboflow like this? And are there alternatives? Again, I really like the assisted labeling and the fact that I don't have to go through the dependency hell that comes with running some random github repo on my local machine. submitted by /u/Snoo_26157 to r/computervision [link] [comments]

Last week was able to test a model of mine in both the model preview and by building a Input > Model > Bounding boxes > Output workflow and inputting a video or image. Now any time i run the workflow it says either 500 or 402 "outputs not found"... Something broken on Roboflow's backend? submitted by /u/draftkinginthenorth to r/computervision [link] [comments]

Going by these instructions: https://developers.snap.com/spectacles/about-spectacles-features/snapML It says we need to use YOLO 7 for the model--but I see roboflow onloy has YOLOv12, YOLOv11, YOLO26, and YOLO-NAS -- can we use any of these? Or is this documentation out of date? submitted by /u/quitebuttery to r/Spectacles [link] [comments]

I made a particle detector (diffusion cloud chamber). I displayed it at a convention this last summer, and was neighbor to a booth that some university of San Diego Professors and students were using computer vision for self-drive RC cars. One of the professors turned me on to RoboFlow. I've looked over a bit of it, but I'm feeling like it wouldn't do what I'm thinking, and from what I can tell I can't run it as a local/offline solution. The goal: to set my cloud chamber up in a manner, which machine learning can help identify and count particles being detected in chamber. Not the clip I included as I'm retrofitting a better camera soon, but I have an in-built camera looking straight down within the chamber. I'm completely new to computer vision, but not to computers and electronics. I'm wondering if there is a better application I can use to kick this project off, or if it's even feasible with the small nature of particle detector (on an amateur/hobbyist level). And what resources are available for locally run applications, and what level of hardware would be needed to run it? (For those wondering, that's form of Uranitite in the chamber). submitted by /u/Funcron to r/computervision [link] [comments]

On a paid account, labelling images of around 12 000 images. It is very slow. Takes about 50-80 seconds to load the images just so that i can start labelling. On each 30th-70th image the site crashes and I need to reload the page, wait for another 50 seconds and then only continue labelling. Is there any other alternative? submitted by /u/New-Artichoke-6875 to r/computervision [link] [comments]

resources: youtube, code, blog - player and number detection with RF-DETR - player tracking with SAM2 - team clustering with SigLIP, UMAP and K-Means - number recognition with SmolVLM2 - perspective conversion with homography - player trajectory correction - shot detection and classification submitted by /u/RandomForests92 to r/computervision [link] [comments]

I have downloaded datasets from roboflow, since roboflow can't take up to 10,000 datasets or more. Is there other alternatives beside from roboflow that I can use for my downloaded datasets from roboflow datasets universe submitted by /u/DirectionEuphoric420 to r/computervision [link] [comments]

submitted by /u/5tambah5 to r/ClashRoyale [link] [comments]