#soms

[elsboom]

Mensen! Ik ben dom, wow. Kom er net pas achter dat Maïzena en cornstarch hetzelfde zijn.

[h8a43va]

get drunk up offa my sound 😻

[gwh0sting]

Silver exists in thrown for a loop and was still Blake's MAIN rival. Riley was just a bonus rival™️ (mirroring sun&moon with Gladion+Hau which makes Riley being that games protag funnier lowkey) that wasn't overly hostile like Silv was

(Big yap under cut ooooo scary)

BBBBUT TFAL's Silver did end up becoming Johto's champion for a while due to Red/Frosty's death on the mountain, with Blake stepping down once he was eventually rescued from the mountain at the cost of Riley's loop being reset again, leading into the current legends-za narrative several years later. Silver then stepped down himself to leave society

Blake didn't tell Silver about the whole thing, though. He kinda just needed to understandably wallow for a while to process what he just went through. Silver was there for him, yeah, but it was at a noticeably large distance. Kinda like a "we don't really know eachother anymore, but just know I'm still here if you wanna talk. We've both experienced loss together despite that, and I don't wanna be that angry person anymore."

Silver spends most of TFAL trying to better himself before he properly rejoins society, and goes a seperate path from Blake to achieve that. But they still have that understanding of loss stemming from Riley's original death. Just an estranged friend trying to redeem himself that'll let you know you can call him

I like to think that he lives with Lance & Leaf (I'm so used to referring to her as Blue but I reserve Blue for the pokespe versions) after cutting ties with Giovanni. He doesn't hate the man, but he realized "hey how i was raised wasn't normal this guy sucks ass" & left on his own terms. oh I could never hate tfal silver even if he doesn't have a big role❤️ my estranged from the narrative guy❤️

[ethanxuu]

Overall Goal

I am building a city model deformation system based on the semantic features of six movies.

The core idea is:

To map the semantic structure of different movies into parameters using SOM (Self-Organizing Map), driving the geometric animation of 17 city models.

The entire pipeline is currently running, and I have completed the deformable animation structure of the model (GeoNodes + point cloud buildings).

The next step is to use the generated control CSV to drive all of this.

Training Data Logic (Data Source → SOM)

(1) Training data comes from the original subtitles (.srt) of six movies.

Read the .srt files of the six movies.

Clean the text: remove timestamps, serial numbers, and punctuation, keeping only English words.

Obtain a set of all words (approximately several thousand words).

Use the CLIP text encoder ViT-B/32 to encode each word into a 512-dimensional vector.

This ensures that the input to the SOM is completely consistent with the text content to be mapped, resulting in a more accurate semantic space.

SOM Training Logic: Semantic Map

(1) The SOM uses a 20×30 grid I wrote myself.

Input: CLIP 512D vectors of all words

Output: A 20×30 semantic topology space (word_som)

Each SOM cell stores a semantic "center vector"

(2) The meaning of SOM

Each word has a semantic position (som_x, som_y)

Similar words are close together (e.g., "memory", "dream", "past"), and words with different semantics are far apart.

This map is the basis for driving the animation later.

Extending SOM to "Sentence-level Semantics"

I needed to find the SOM position for "each line of dialogue", so I did the following:

(1) Parse each line of subtitles

Remove the subtitle number and timestamp

Extract line by line

A total of several thousand lines of dialogue (six-film corpus) were obtained.

(2) For a single line → All words → Find their positions on the SOM

Cleanse a sentence into multiple words

Find each word's position on the SOM (som_x, som_y)

Take the average of these word positions as the semantic center of the sentence (float is normal)

(3) Obtain the final sentence-level SOM annotation table

The final generated data is:

movie, line_id, line_text, som_x, som_y, emotion

This CSV is the "semantic feature library driving the animation".

City Model Deformation Animation (Completed)

I have completed this part:

I built 17 city modules (point cloud building form) in Blender

I created a deformable system (Geo Nodes)

I introduced various animation control parameters such as noise, scaling, rotation, and translation

All models can be uniformly controlled on the timeline

It is now possible to generate dynamic effects of city morphology changing with parameters

That is to say: the city model can deform, push, rotate, and breathe, but it is not yet semantically bound.

The core next step: Driving animation with CSV

The next task is clear:

I need to map the previously generated SOM+emotion table (movie semantics) into animation control parameters.

This includes:

scale (zoom in/out)

loc_x / loc_y / loc_z (displacement)

rot_z (rotation)

noise_val (Geo Node noise intensity)

The logic is as follows:

Normalize som_x, som_y, and emotion

Set different parameter ranges for each movie (determining style)

Generate a movie_driving_params.csv file

Batch read using Blender + automatic keyframe insertion

This achieves:

Different movies → different semantics → different deformation methods for city models

[almondrootwc]

soms

[gluechugger]

Running around in circles screaming about fallout 4 Arthur

[electronicsbuzz]

Forlinx Embedded | A Glorious Retrospect of electronica China 2025

electronica China 2025 grandly opened at Shanghai New International Expo Centre. This exhibition gathered over 1,800 Chinese and internation