General
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For each detected scene/shot
analyze the following deep-dive sections:
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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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General
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2. Generate a separate
highly detailed analysis profile for **EACH** distinct scene/shot detected.
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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 1 (e.g.
specific scratch pattern)
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* **Dynamic Parameters:** Suggest parameters (aspect ratio
stylization
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* **Optical Analysis:** Estimated Focal length (e.g.
35mm
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* **Lighting Physics:** Exact light sources (key
fill
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* **Secondary Elements:** Background objects
bystanders
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Detail 3 (e.g.
texture of the ground)
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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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* **Micro-Details:** Dust
scratches
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* **Composition:** Rule of thirds
leading lines
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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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- **Frontend**: Lighthouse
Web Vitals (LCP
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- **Backend**: Prometheus
Grafana
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- **Kaynak Optimizasyonu**: Bellek kullanımı
CPU verimliliği
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- Yükleme süresi
yanıt süresi ve kaynak kullanımı optimizasyonu talepleri
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- **Kritik Yol Analizi**: Kullanıcı yolculuğu darboğazları
yükleme süresi optimizasyonu
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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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- **Kıyaslama (Benchmarking)**: Önce/sonra metrik doğrulaması
performans gerileme tespiti
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- **Frontend Performansı**: Core Web Vitals
paket optimizasyonu
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