Art & design — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 17 September 2026 and assigned it the closest of 31 fixed categories, at 89% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.
Growth
14 measurements spanning 59 days, net +188. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 1,305–1,549 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
23 Oct 2026, 14:57
1,521
+2
20 Oct 2026, 16:35
1,519
+3
18 Oct 2026, 02:39
1,516
+6
14 Oct 2026, 23:55
1,510
+34
11 Oct 2026, 08:37
1,476
+52
4 Oct 2026, 21:37
1,424
+49
25 Sept 2026, 15:19
1,375
+8
15 Sept 2026, 07:38
1,367
+8
11 Sept 2026, 11:39
1,359
+10
6 Sept 2026, 16:38
1,349
-1
1 Sept 2026, 21:48
1,350
+6
29 Aug 2026, 15:37
1,344
+8
26 Aug 2026, 17:28
1,336
+3
25 Aug 2026, 23:31
1,333
first reading
Engagement
13 posts held, back to 19 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 13 posts for this entry, the most recent from 25 August 2026. An engagement rate over an empty window would be a number about nothing.
Reaction mix
505 reactions across 13 posts, in 9 distinct kinds. The most used accounts for 54.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
273
54.1%
🔥
108
21.4%
😁
71
14.1%
👍
44
8.71%
💘
4
0.792%
🆒
2
0.396%
🤩
1
0.198%
🥰
1
0.198%
🫡
1
0.198%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 13 of the 13 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 505 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 13 most recent posts we hold, published 19 August 2026 to 25 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
دوتا قاب پایین صفحه در واقع میخواد یک حرکت دوربین رو نشون بده یه جورایی معادل پَن در سینما، اما از اونجایی که مازوچلی محدودیت قائل بوده برای خودش ، از طریق دودی که وارد قاب سمت راست شده ، و همچنین سر کاراکتر ، در واقع داره دوتا پنل رو بهم پیوند میزنه . بر خلاف دوتا قاب قبلی که دو برداشت متفاوت از کاراکتر داشتیم .
فریم یا فریمهای میانی رو حذف کرده ، اما حرکت و پریدن کاراکتر کماکان حس میشه.
درسهایی که میشه گرفت.
چطور …
ببینیم میتونیم چه درسهایی از
David Mazzucchelli
توی این صفحه یادبگیریم.
تقریباً هر پنل رو طوری طراحی کرده که جهت حرکت چشم خواننده با حرکت شخصیت همراستا بشه ، بدن Daredevil در هر لحظه یک silhouette بسیار خوانا داره. حتی اگر دیالوگها رو پاک کنیم، میتونیم اتفاق رو بفهمیم.
اول ایده بعد روایت بعدش کادر و ژست و فرم و بعد هرچقدر آناتومی لازم بود.
نه اینکه:
آناتومی ، فیگور ، طراحی ، رندر ، خب حالا ببینیم چی میشه.
یه چیزی رو در انتها اضافه کنم ، و اونم اینکه من متوجه نمیشم چرا زمانی که داریم طراحی آناتومی رو یادمیگیریم و قراره جای عضلات و فرم و مکانیکشون رو یادبگیریم باید از کسی مثل میکل آنژ بگذریم با اون حد از داینامیک بودن کارهاش و بریم سراغ پروکو یا امثالهم؟
منظورم از قیاس میکل آنژ و پرو…
جواب سختتر میشه. یه چیز دیگه هم هست که فکر میکنم برای کمیک خیلی مهمه: کمیک بیشتر از اینکه دربارهی کشیدن بدن باشه، دربارهی بازی دادن بدنه. یعنی بدن برای تو باید تبدیل بشه به بازیگر. این آدم خستهست؟ ترسیده؟ داره دروغ میگه؟منتظره؟داره چیزی رو پنهان میکنه؟میخواد بره ولی نمیتونه؟اینجا حتی یه فیگور ساده و از نظر آناتومی ناقص میتونه خیلی بیشتر از یه فیگور کاملاً صحیح حرف بزنه.
و یه دام دیگه هم هست:
وقتی خیلی زیاد ب…
اینا چیزایی نیستن که با یاد گرفتن آناتومی حل بشن.
مثلاً ممکنه یه نفر فیگور رو فوقالعاده درست بکشه، ولی وقتی شخصیت رو میذاره توی یه تصویر، هیچ اتفاقی نمیافته.
در عوض یکی مثل Robert Valley ممکنه بدن رو عمداً عجیب و غیرواقعی بکشه، ولی تصویرش یه چیزی داره که تو رو میگیره. چون برای اون درست بودن بدن هدف نیست؛ تصویر و روایت هدفه. به نظرم یکی از خطرهای مدل آموزش Proko اینه که آدم کمکم به یه جور مهارت عمومی و قابل قبو…
🔴سوال پر تکرار
سیستم یادگیری طراحی با سبک و سیاق proko و کلا این دست طراحی آیا خوبه یا بد؟ نظر من اینه که کلاً این مدل آموزشها بد نیستن،ولی برای هدف خاصی ساخته شدن و اگه هدفت تصویرسازی و کمیک باشه یا انیمیت فریم بای فریم یا استوری بورد ، یه جایی میبینی داری کلی چیز یاد میگیری ولی اون چیزی که میخوای، یعنی تصویر ساختن الزاماً جلو نمیره.
مشکل اصلی اینه که این سیستمها خیلی روی این تمرکز دارن که: بدن رو بفهم، فرم رو…
SPA
در واقع یه هیولای بزرگ نیست که آدمها باید شکست بِدنش خودِ سیستمِ رفاه، مصرفگرایی و تبدیل به یک کابوس شده.
هتل قرار محل آرامش، پاکیزگی و فرار از مشکلات زندگی باشه، ولی دقیقاً همون چیزایی که آدما میخوان از اونا فرار کنن، به شکل کپک، بیماری، هیولا، بدنهای دفرمه و ارواح از داخل هتل بیرون میزنن.حتی زوج اصلی در نهایت خودشون گرفتار همون چیزی میشن که از اون فرار کرده بودن.
اما از همون اول ماجرا یه چیزی توی هتل درست نیست.
یه رطوبت سیاه و چسبناک توی راهروها و دیوارای هتل ظاهر میشه و آروم آروم همه جا رو میگیره. بعد کپک و بیماریهای پوستی، توهم، ارواح و موجودات عجیب شروع به ظاهر شدن میکنن. همزمان یکی از مهمونای VIP ناگهان ناپدید میشه. آدمهای مختلف هم توی هزارتوی هتل گم میشن یا با اتفاقات عجیب غریب روبهرو میشن.نکته جالب اینه که آدمای هتل تقریباً به اندازهای که باید، به این وحشت واک…
🔥9❤7👍2
Showing the 12 most recent of 13 posts we hold for @rezaabbbasii. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
فردوسیخوانی @readingferdowsi · 32,009 Telegram ranks this channel #10 of 78 here — alongside 77 others — read 10 September 2026
This channel appears in 1 seed channel's Telegram-generated recommendation list in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 23 October 2026 — this
entry's latest reading, not the date you are reading this.
“رضا عباسی|مدرسه ی طراحی” (@rezaabbbasii), 1,521 subscribers as measured 23 October 2026. Telegram Register, tgregister.com/channel/rezaabbbasii.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.