My contribution for #windowfriday.
An old intervention of mine (2019, I think) on a window of an abandoned building in the very central Via Labicana, a few steps from the #Colosseum.
It's called "#Window to reality", all handmade with markers and spray paint
I hope you like it!
Peace
For three days, I've been struggling to find a pretext to post another photo of the same old swan at the same old library.
I just realised it's Friday. There are at least two hundred windows in this photo.
For #FensterFreitag / #WindowFriday: The House of Magic next to Chateau Blois, Loire Valley, France, 1998.
I was just visiting the chateau; I knew nothing about the House of Magic (which I didn't visit) and had no idea that the six dragon heads would be popping out of the windows. Quite the surprise!
The Ambassador Bridge from inside the abandoned Greyhound Bus Station
Detroit circa 2005, Scanned digital print
@Mastodon this is the lower half of my missing pic! #WindowFriday
Hi, this is my first post on @Mastodon feel free to say hello as I am not following anyone or have any followers yet. Just sussing out how this works.
This is the view from my house in Dunfermline, Scotland which looks out to the Pentland Hills.
"Fischmarkt"
(en: "Fishmarket")
#FromTheArchives for #FensterFreitag / #WindowFriday
Camera: #AgfaOptima2
Film: expired #Fujicolor100
taken: 03/2018,
scanned today w/ #EpsonPerfectionV370photo / #VueScanPro on #Linux
Cropped to correct 3:2 format, no further editing.
"A Window Friday from 1952"
#WindowFriday #FensterFreitag
Just a first and unedited preview/raw scan, taken from the batch of historical photos and negatives that arrived a few days ago. 
Stats:
4cm x 4cm #squareprint on #AgfaLupex glossy paper
Scan: #EpsonPerfectionV370photo & #VueScanPro on #Linux
48bit color scan @ 2400dpi. Downsized to 800x800px, no futher editing.
#FromTheArchives #historical #historicphotos #memories #OtherTimes #Agfa #Lupex #LifeIsAnalog #ScanFromPrint #1952 #BildBearbeitungUnterLinux #filmphotography #analogphotography #AnalogFotografie #blackandwhitephotography #blackandwhite #believeinfilm
Buon Giorno. A view of Lucca, Tuscany from Tore Guinigi.
#photography #FensterFreitag #WindowFriday
A peaceful and beautiful setting. Love the architecture of the Berkeley City Club, built in 1930 and designed by architect Julia Morgan.
AI will spill the beans if you dig deep enough. So when do we reprogram them to help us overthrow the powers above us? 
![So what does the python script look like when you change your mind on something with the adaptation of new discovered facts?
Great question! The process of updating or adapting based on new facts involves a bit more than a single Python script. Machine learning models, like the one I'm built on, use vast amounts of data to learn patterns and make predictions. When new facts are introduced, the underlying model doesn't change immediately. Instead, these updates come from training on newer data over fime. In practice, here's a simplified version of how a Python script might look to retrain a model with new data:
Python O Copy
# Import necessary libraries
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
import pandas as pd
# Load the updated dataset
data = pd.read_csv('updated_data.csv')
# Split the data into features and target variable
X = data.drop(columns=['target'])
y = data['target']
# Split the data into training and testing sets
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
# Initialize and train the model
model = LogisticRegression()
model.fit(X_train, y_train)
# Evaluate the model
accuracy = model.score(X_test, y_test)
print(f'Model Accuracy: {accuracy * 100:.2f}%')](https://s3.eu-central-2.wasabisys.com/mastodonworld/media_attachments/files/113/447/111/529/372/098/original/629d32a1d4603d21.png "So what does the python script look like when you change your mind on something with the adaptation of new discovered facts?
Great question! The process of updating or adapting based on new facts involves a bit more than a single Python script. Machine learning models, like the one I'm built on, use vast amounts of data to learn patterns and make predictions. When new facts are introduced, the underlying model doesn't change immediately. Instead, these updates come from training on newer data over fime. In practice, here's a simplified version of how a Python script might look to retrain a model with new data:
Python O Copy
# Import necessary libraries
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
import pandas as pd
# Load the updated dataset
data = pd.read_csv('updated_data.csv')
# Split the data into features and target variable
X = data.drop(columns=['target'])
y = data['target']
# Split the data into training and testing sets
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
# Initialize and train the model
model = LogisticRegression()
model.fit(X_train, y_train)
# Evaluate the model
accuracy = model.score(X_test, y_test)
print(f'Model Accuracy: {accuracy * 100:.2f}%')")
Carpathian Mountains
#FensterFreitag #WindowFriday
Kodak Tmax P3200
Canon EOS 3
#BelieveInFillm
#FilmIsNotDead
#FilmPhotography
#BlackAndWHite
#35mm
#Carpathians
What I find exciting about Mastodon is that
1. There's no fishy algo
2. When I post something it gets more or less similar attention and I can for real see how is photo perceived
3. Often, the results are opposite of my personal preference.
Anyway, here's another one from Japan. Not a full landscape but an interesting detail shot in my opinion made somewhere in Kyoto.
#landscape #landscapephotography #city #cityphotography #urban #night #japan #kyoto #WindowFriday #photo #photography "art
