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Vivosun Grow Camera Photo Contest

- Name your photos with health status (e.g. Powdery Mildew, Mold, Bud Rot, Spider Mites, Aphids, Thrips, Nutrient Issues) or growth stage (e.g. Germination, Seedling, Vegetative, Flowering, Harvest).- Photos from a grow camera.- Multiple entries encouraged.- Indoor growing photos only. - Open worldwide. Alternative prizes will be arranged if shipping is unavailable.

Vivosun Grow Camera Photo Contest

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211 Photos participating
2mo
44 comments

If you have a grow camera in your tent, this contest is for you.We’re building an AI learning resource for the entire smart growing community — and we need real photos from real growers. Share what your camera captures: healthy plants at any growth stage, pest damage, nutrient deficiencies, disease symptoms, etc. All submitted photos will contribute to our AI model training and growcam development.Whether you’ve grown with Vivosun before or have never heard of us — your contribution matters.

 

 

 


List of prizes:1st Prize (1 winner): Vivosun AeroLight 350W or AeroLight 550W2nd Prize (1 winner): Vivosun X42 GrowHub Controller3rd Prize (3 winners): Vivosun AI GrowCam Pro

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squalino
squalino commented20d ago
bonjour je ne sais pas comment vous voulez qu'on si prennent pour tous d'écrire. je ne suis même pas sûr de ce qu'il ont eu .à 100% photo 1 e mauvais ph remarqué à temps photos 2 mauvais ph de l'eau photos 3 et 4 blocage absorption nutriment et mauvais ph photos 5 micro fissure lors du lst photo 7 et 8 sénescence 10 moucherons de terreau photos bud orange . oxidation du à l'exposition continue à la lumière fox tail
ATLien415
ATLien415 commented19d ago
@Ivy_Vivosun , To be clear...the submissions for this competition will be used as training data for your AI resource? What is that going to mean? Who is labelling this set/what is the purpose of the user submitted label? There are some amazing free, locally ran image processing models that are ubiquitous in industrial applications. Something like that on board with a context layer to integrate into some type of bounded LLM on your hubs would be interesting. The newest folks in this space are taking non-visible light spectrum for more fun. My questions are this... Why crowdsource this data? Isn't the veracity of this data the issue in the first place.......or else ChatGPT would be diagnosing plants accurately. The simple fact is that these online spaces like Reddit and whatnot are going to give you a picture of N toxicity and you'll have 5 distinct answers and people ready to draw weapons over "their" response, only one of which was correct. Data labelling for anything of pedigree which isn't just common knowledge...it is a job description, and it pays particularly well in most circumstances. It also has an extreme bar to clear for both accuracy and precision. I just have questions. Like for example, when yall crowdfunded your Vcure. You made a whole lot of marketing noise about an "inverted compressor" which is fine. Compressor-driven devices run on exploiting work cycles and you can invert that, which is a common thing. I'm still not sure about the "inverted compressor" itself as to the device but from my understanding it is a compressor-driven device. Why make that design choice? From my viewpoint, yall dropped a crowdfunded cabinet that looks like a Cannatrol but ignores the entire point of the design. Dew point modulation for permanently mold theory, aka the orthogonal feedback loop is just half of the story. The other half was and is trichome integrity. How are you maintaining trichome integrity with a compressor?
Antifame
Antifame commented17d ago
@ATLien415, Those are very interesting points you're raising. I wonder what—or if—they would say in response. 😎
Ivy_Vivosun
Ivy_Vivosun commented12d ago
@ATLien415, Great questions! The level of technical depth here is exactly the kind of feedback we find most useful, so thank you for taking the time. On the AI GrowCam data pipeline: To clarify, user submissions are not directly used as training data. We operate a multi-stage data pipeline: User submissions (images + metadata) Automated quality filtering Model-assisted pre-labeling Human validation (internal or expert-reviewed) Consensus-based verification This ensures that only high-confidence, structured data enters the training set. Regarding crowdsourcing: the goal is not to replace expert knowledge, but to expand coverage of real-world variability — including lighting conditions, plant stages, and rare edge cases that are difficult to capture in controlled datasets. We also explicitly model label uncertainty using techniques such as consensus labeling and confidence-weighted training, rather than assuming a single "ground truth" per sample. Finally, general-purpose models are limited in this domain due to lack of specialized data and fine-grained visual understanding. Our focus is on building a domain-specific system with a continuous data feedback loop, rather than relying solely on off-the-shelf models.
Ivy_Vivosun
Ivy_Vivosun commented12d ago
@ATLien415, On the VCure and compressor design: This is a compressor-driven system. The design choice over semiconductor cooling comes down to power, precision, and longevity — variable-speed compressor technology gives us tighter environmental control with better durability over time, paired with our own algorithm managing internal condensation to maintain stable conditions. On trichome integrity specifically: The mechanism isn't about any single feature. It's about eliminating the environmental volatility that causes damage in the first place. Hang drying and traditional curing expose material to fluctuating temp and humidity, which causes trichome stalks to become brittle and increases fracture risk significantly. By holding both tight throughout the entire post-harvest window, along with consistent gentle airflow, we're keeping the gland structure stable without physical contact at any stage.
ATLien415
ATLien415 commented12d ago
@Ivy_Vivosun, I must say this is much more information than I expected, and I genuinely appreciate it. My first reaction to this is curiosity. Managing condensation is managing dew point, so the same as logic as the Cannatrol. This is expected as this is the same logic for antiques/books/meats/cheeses/and more. I can see how from an engineering standpoint a first pass would be where the raw power is (compressors). Does this not have some impact on the local environment? From my understanding, and this is my words of whitepapers that have been reproduced, is that trichome cuticles measure a couple molecules thick and that things on the order of vapor pressure gradients (essentially invisible waves caused by things like compressors) were enough to rupture heads...especially in dry/cure. Ruptured heads leak, and by that mechanism you lose secondary metabolite mass. The Cannatrol team has had this finding of increased trichome integrity both by reproduced manual gridding/counting of heads and a (novel?) chromatography method. Have yall confirmed that you are on the same order increase as Cannatrol? Granted, a TEC will never last as long as a compressor device...a TEC doesn't mechanically change the environment of the flower when I think about how the device functions. I guess that is my original concern with the design and something folks like myself have questioned since the announcement until now.
ATLien415
ATLien415 commented12d ago
@Ivy_Vivosun, Sounds rigorous. 👌 Mmmm boundary value cases and real-world variability make a lot of sense. When I was referring to available models, I mean more of academic machine learning models specifically for image classification that are open-source. I would also be hesitant to grab a vendor model off the shelf in the current environment as well. Will Vivosun be keeping the community updated on this AI GrowCam?
Ivy_Vivosun
Ivy_Vivosun commented7d ago
@ATLien415, The AI GrowCam is currently in the crowdfunding and development phase. We'll be posting product updates on our crowdfunding page as things progress, so that's the best place to follow along: 👉 https://www.vivosun.com/crowdfunding/growcam-ai
MrBulldops
MrBulldops commented21d ago
My picture was during veg stage and shows phosphorus deficiency.. had to type it in comments
MrBulldops
MrBulldops commented20d ago
@Ivy_Vivosun, I can’t edit, withdraw, or add a new photo because the buttons are gone
Comment by MrBulldops photo #1
Ivy_Vivosun
Ivy_Vivosun commented20d ago
@MrBulldops Hi there, the bug should be fixed now! Please try again😊
MrBulldops
MrBulldops commented20d ago
@Ivy_Vivosun, I added my photo to files then changed the file name with the deficiencies and stage but it looks the exact same.. hope that’s correct and I apologize for sending g so many messages
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Paul_on
Paul_on commented19d ago
My photos are in , mostly flowering shots ,some fading some not ,and 1 or 2 green vibrant shots . The leaves that look deficient are in late flower, thats why they look a little different. Thanks Vivosun 🍀👍
GERGrowDesigns
GERGrowDesigns commented19d ago
Nice Contest🌱
MrH20
MrH20 commented10d ago
My grow diary from seed to ashes.
in_a_few_weeks
in_a_few_weeks commented11d ago
2 Weeks before harvest! It was a good run. AeroZesh G8 / 200mm with 8 inch Vivosun active carbon filter and Fecida Lights.
ProfessorWeed
ProfessorWeed commented14d ago
Fraspuren Von Blattlaus (Weise Gänge) auf Blatt Oberseite
Raw_TDS
Raw_TDS commented18d ago
Algumas fotos do meu primeiro ciclo comprei todos os produtos da vivosun e desde então venho acompanhando o crescimento da empresa muito fodaa, o jeito que eles colocam tecnologia com cultivo algumas imagens das minhas plantas que estão em flora
00110001001001111O
00110001001001111O commented3d ago
If this weren't for a product they will eventually make money from, i'd be all about contributing... corporations get enough handouts as is. They should be paying people for their expertise... because once the AI model is properly trained that expertise is then worthless. Like training your replacement at work... no future in that.
CAZZ68
CAZZ68 commented5d ago
Beautiful fade on this Sour Durban
Antifame
Antifame commented20d ago
My pictures show Thrips/Tacoing/Canoeing. It's not possible to tag the photos. Also the website bugged out after uploading my first few pictures. The button to "join" disappeared. When I click where it was before the website goes 404. 💩
Webacca
Webacca commented20d ago
@Antifame, immo is hier alles massiv verbuggt. Bei mir stimme uploads nicht und die site stellt immer auf englisch und autotranskate um.... Zum kotzen
Antifame
Antifame commented20d ago
@Webacca, leider Dauerzustand. Man kann nur hoffen, dass es irgendwann besser wird.
Ivy_Vivosun
Ivy_Vivosun commented20d ago
@Antifame Hi there, the bug should be fixed now! Please try again😊
in_a_few_weeks
in_a_few_weeks commented11d ago
My Plants where in Flowering Phase. Everything was fine. The first plant on the left got a massive Cola Bud. I was afraid that it could mold. But nothing happend. The harvest was great. AeroZesh G8 / 200mm with 8 inch Vivosun active carbon filter and Fecida Lights.
in_a_few_weeks
in_a_few_weeks commented11d ago
Vegetation Phase from the Lemon Mandarin. One plant got a light nitrogen deficiency but i fixed it.AeroZesh G8 / 200mm with 8 inch Vivosun active carbon filter and Fecida Lights.
in_a_few_weeks
in_a_few_weeks commented11d ago
The Lemon Mandarin harvest was heavy! Not Popcorn Buds or rot. Healthy Plants at the end. AeroZesh G8 / 200mm with 8 inch Vivosun active carbon filter and Fecida Lights. Got some gnats the whole grow, it was the first and the last time i used biobizz soil.
GingerGarageGrow420
GingerGarageGrow420 commented13d ago
There’s a lot of healthy grows in here and some nice even canopies! Good job gromies 🌱👏
BarneyRumble420
BarneyRumble420 commented14d ago
My photo, early flowering stage
ProfessorWeed
ProfessorWeed commented14d ago
Trockenstress
ProfessorWeed
ProfessorWeed commented14d ago
Blattläuse
ProfessorWeed
ProfessorWeed commented14d ago
Die weisen Punkte auf den Blättern sind Überreste von verpupungen von Blattläusen