View allAll Photos Tagged Normalizes

3264

2448

pixel

     

-1728707843

311

1

  

0.310

0.078

normalized

0.355

0.104

 

Face

   

-1728707843

255

2

  

0.366

0.069

normalized

0.462

0.092

 

Face

2018 Detroit Veterans Day Parade

3264

2448

pixel

     

-1549955955

323

2

270

  

0.458

0.150

normalized

0.259

0.200

 

Face

How do you change MKV Media Contrast Normalize Clip contrast example without ffmpeg command in Win7 10 Computer.

2018 Detroit Veterans Day Parade

2018 Detroit Veterans Day Parade

2018 Detroit Veterans Day Parade

3264

2448

pixel

     

1551505303

161

1

  

0.558

0.066

normalized

0.531

0.087

 

Face

   

1551505303

265

  

0.483

0.069

normalized

0.422

0.092

 

Face

1. SI: People have learned to normalize the bad state of streets and communal spaces, leading to a scarcity of caring to fix them.

 

2. Materials: Planting area with weeds filled with poop.

 

3. Idea: This planter is full of dog poop, which means both the church and the dog owners don't pick it up.

 

4. Process: The poop is clearly shown in this shot and wrapped in a bed of weeds.

3264

2448

pixel

     

388178208

339

2

270

  

0.718

0.084

normalized

0.417

0.112

 

Face

2018 Detroit Veterans Day Parade

On the left, a visualization of four source files from our "old school" programming department... on the right, four source files from the "new school."

 

The graph height (normalized across all the graphs, hence the lack of y-axis labels) represents indentation level at any given source code line (denoted by the x-axis labels).

 

Our "old school" code has an *immense* problem of both being far too verbose per file (8000 lines? Seriously?) and far, *far* too complex per function. The comparison is a bit contrived, as our new codebase lacks even a single 8000-line file, but I've thrown in one of the "ugliest" source files in our new codebase at the bottom of the "new school" graphs to show that even in our most complicated source, we're never writing 1000+-line functions that nest functional blocks 10 or 15 levels deep.

 

Interesting structures to look for: any long stretches where the graph line doesn't return to the baseline (denoting a function or a functional block that continues without break); and visual structures that "look" the same (have the same profile)... the "old school" programmer(s) tended towards *rampant* code "reuse" (and by reuse I mean copy/paste), so you'll tend to see very similar-looking structures in a lot of the graphs on the left-hand side.

 

Just an aside: pay little mind to this exposition, as I was just mucking around with Google Charts and the idea of putting together some type of alternative code metric. For an few hours work, I think it came out pretty well.

 

Check Picasa for super-full-sized version.

 

Update 02/01/08: Original version of the script had a bug that accounts for some of the "reticulating" spikes seen... will try to post a new version of this image generated with the new script "soon".

 

Speaking of the script, here is the source (with the aforementioned bug and a few others fixed). Like I said, it was whipped up in a few hours, so it's not the prettiest nor the most well-written, but it works!

 

Update 02/04/08: uploaded newest version of the script (rev 1778), which changes the default behavior to count indentation level by looking at brackets, rather than simply the amount of indentation per line. Makes for much smoother charts; will hopefully re-post this image after running through the new script soon!

 

2018 Detroit Veterans Day Parade

3264

2448

pixel

     

-1381969974

288

16

210

  

0.587

0.194

normalized

0.684

0.258

 

Face

   

-1381969974

311

17

180

  

0.760

0.172

normalized

0.895

0.229

 

Face

   

-1381969974

18

264

45

180

  

0.410

0.178

normalized

0.311

0.237

 

Face

2018 Detroit Veterans Day Parade

New Project I'm starting to normalize conversations about homelessness and how each of us can do our part to help.

2018 Detroit Veterans Day Parade

All the shots are unique, you haven't seen them earlier and were not processed from published ones!

 

These shots were made with Pentax KF B&W Orange settings. Not IR as for shots with black sky to add a pinch of doom scenario or apocalyptic emotions. Time to find out what's good in traditional b&w shots. Both other series and this one were accompanied with CPF.

 

What I did was normalizing central gray scope here to make the shots look similar. I'm aiming to discover camera sets to make shots without need to post process them, if that would be possible, or with minimalist touches of my GIMP.

 

I did not touched black slider. Gray (+/-), white (-) and highlight (-) sliders only, plus conservative values for sharpness (only for compensation of camera soft settings): Radius: 1.000, Amount: 0.310 and Threshold: 0.110.

 

I ask you for comments what to check, what to correct and how,

and which compositions look better using such bright settings for shooting b&w with strong day light. Any suggestions are welcome and highly appreciated.

 

Thank you. :) Have a nice fun here. :)

May 3, 2016: Over the last six months, risks to global financial stability have risen, according to the International Monetary Fund’s April 2016 Global Financial Stability Report. In advanced economies, the outlook has deteriorated because of heightened uncertainty and setbacks to growth and confidence. Disruptions to global asset markets have added to these pressures. Declines in oil and commodity prices have kept risks elevated in emerging markets, while greater uncertainty about China’s growth transition has increased spillovers to global markets. These developments tightened financial conditions, reduced risk appetite, and raised credit risks, weighing on financial stability. The situation in markets appears significantly improved, but is the turmoil of the past months now safely behind us, or is it a warning signal that more needs to be done to secure financial stability? The IMF’s April 2016 GFSR addresses this key question and many others.

3264

2448

pixel

     

26316095

235

3

270

  

0.527

0.059

normalized

0.345

0.079

 

Face

Photographs from Harnhill for the DART project collected by Robert Bewley on 12th April 2011

3264

2448

pixel

     

1842781619

148

2

270

  

0.637

0.069

normalized

0.316

0.092

 

Face

2018 Detroit Veterans Day Parade

This was for my AP concentration. I wanted tot normalize cannibalism and anthropophagy by focusing on the emotions and reasons instead of the act itself. This picture was to represent for the cultural/tribal side of the act.

3264

2448

pixel

  

-988911111

6

325

315

270

  

0.542

0.219

normalized

0.222

0.292

 

Face

2592

1936

pixel

     

944800032

260

28

270

  

0.454

0.043

normalized

0.460

0.058

 

Face

0.445670

0.062500

0.909314

0.083333

normalized

 

Face

 

0

0

308

12167206267420

10

     

2448

3264

pixel

3264

2448

pixel

     

-1016586112

278

26

270

  

0.441

0.231

normalized

0.422

0.308

 

Face

Photographs from Harnhill for the DART project collected by Robert Bewley on 12th April 2011

2018 Detroit Veterans Day Parade

2018 Detroit Veterans Day Parade

3264

2448

pixel

     

1751447799

90

6

270

  

0.704

0.056

normalized

0.650

0.075

 

Face

Back down again. Getting my heartbeat normalized. These hats were somewhat different from my sweat-soaked baseball cap.

2448

3264

pixel

     

1629949196

1

333

0

270

  

0.299837

0.324755

normalized

0.409007

0.433006

 

Face

Doing a test of all of the filters in MOLO Filters Pro for the Palm Pre.

This is the Normalize filter.

1 2 ••• 55 56 58 60 61 ••• 79 80