General
PromptBeginner5 minmarkdownQuality: 20
For each detected scene/shot
analyze the following deep-dive sections:
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General
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* Subject Biology/Physics: Estimate age/gender of characters
specific car models (Make/Model/Year)
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General
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* Object Inventory: List distinct key objects present (e.g.
1 vintage Rolex watch
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General
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2. Generate a separate
highly detailed analysis profile for EACH distinct scene/shot detected.
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General
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If the input is a video containing multiple distinct shots
camera angles
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4. Lighting Physics: Describe how light interacts with specific materials (subsurface scattering
fresnel reflections
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3. Text & Symbol Detection: Identify any visible text
logos
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Detail 3 (e.g.
texture of the ground)
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* Dynamic Parameters: Suggest parameters (aspect ratio
stylization
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* Micro-Details: Dust
scratches
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* Lighting Physics: Exact light sources (key
fill
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* Surface Definition: Differentiate materials rigorously (e.g.
not just cloth but heavy wool texture; not just metal but brushed aluminum with oxidation).
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* Composition: Rule of thirds
leading lines
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* Secondary Elements: Background objects
bystanders
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* Scene Context: Estimated time of day
location type
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Detail 2 (e.g.
light reflection in eyes)
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Detail 1 (e.g.
specific scratch pattern)
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* Optical Analysis: Estimated Focal length (e.g.
35mm
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- Kıyaslama (Benchmarking): Önce/sonra metrik doğrulaması
performans gerileme tespiti
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- Kritik Yol Analizi: Kullanıcı yolculuğu darboğazları
yükleme süresi optimizasyonu
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General
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- Backend: Prometheus
Grafana
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Education
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- Veritabanı: EXPLAIN ANALYZE
Slow Query Log
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General
PromptBeginner5 minmarkdownQuality: 24
Önce ölçün
sonra optimize edin. Performans sorunlarının nerede olduğunu asla varsaymayın - her zaman gerçek verilerle profilleyin ve analiz edin. Erken optimizasyondan kaçınarak
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General
PromptBeginner5 minmarkdownQuality: 20
- Kaynak Optimizasyonu: Bellek kullanımı
CPU verimliliği
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