Jayanta Bhai
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📈 Análisis del canal de Telegram Jayanta Bhai
El canal Jayanta Bhai (@jayantabhai06) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 103 055 suscriptores, ocupando la posición 115 en la categoría Arte y diseño y el puesto 2 540 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 103 055 suscriptores.
Según los últimos datos del 21 septiembre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 896, y en las últimas 24 horas de -24, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 11.38%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 3.20% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 11 727 visualizaciones. En el primer día suele acumular 3 296 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 8.
- Intereses temáticos: El contenido se centra en temas clave como editing, background, dialogue, edit, cartoon.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“This Channel is all about Video & Photo Editing Tutorial's”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 22 septiembre, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Arte y diseño.
103 055
Suscriptores
-2424 horas
+137 días
+89630 días
Archivo de publicaciones
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Trending Car Driving Ai Video Editing Prompt | Instagram Trending Pata Chalega Song Reels Editing - 100% Freee
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Instagram Trending Velocity Video Editing | Velocity Video Editing In Capcut | Capcut Editing
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Trending Cute Ghost Girl Dance - Bike Reels Editing | Full Breakdown
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103 055
Trending SRK Dance Ai Video Editing | Shahrukh Khan Dance Ai Video Kaise Banaye | Ai Video Editing
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Prompt 2—-
Photorealistic cinematic portrait of a beautiful young Indian woman in a white-and-red Bengali saree with ruffled border, traditional gold jewelry, barefoot, standing gracefully beside ancient stone temple pillars and steps. Soft golden-hour sunlight, warm sun rays, flowing black hair, serene downward gaze, natural expression, shallow depth of field, dreamy bokeh, DSLR photography, ultra-detailed, 8K, vertical 4:5.a big durga idol in background in hazy.kans grass in hand.
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Prompt 1–
A vintage-inspired
Bengali aesthetic portrait of a girl wearing a white saree with a red border and a red blouse, her saree pallu flying high in the windy environment with retro grace. She has a tiny maroon bindi, subtle makeup and reddish-brown wavy hair flowing gently. Holding unbloomed lotus flowers in her hands, she stands calm, happy yet introspective, in front of a massive half-made muddy Durga Maa idol at Kumortuli, where sunrays fall divinely upon the sculpture.
The background is slightly blurred and muted in tone, while she remains colorful, sharp, and radiant, embodying the soulful agomoni essence of Durga Puja with an aesthetic, vintage, and timeless charm. Keep the girls face 100% same without any alterations. 3:4 ratio
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Instagram Trending Durga Puja AI Photo Editing Prompt | Durga Puja Ai Photo Editing | ChatGPT
Video direct Link 🔥👇🏻
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103 055
Instagram Trending Ganesh Chaturthi AI Photo Editing Prompt | ChatGPT AI Photo Editing
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103 055
Trending Master JD Entry AI Video Editing Tutorial | Master Movie Ai Video Editing Prompt | Ai Video.
Video link🔗
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Video prompt ——
Three friends reunite on vintage motorcycles, singing joyfully on an Indian country road in an authentic, hyperrealistic 1980s film scene. Generate an Indian rural two-lane asphalt road with dusty shoulders, lush shrubs, trees, fields, simple utility poles and sagging wires under a bright cloudy sky. The riding stretch is clear. Render real skin, woven fabric, worn rubber and vibrating metal. @Image1 = Friend1 face; @image2 = Friend2; @image3 = Friend3 face. @bike1 = Friend1 bike1; @bike2 = Friend2 bike2; @bike3 = Friend3 bike3. Preserve distinct identities and each bike's design, color and mechanics. All are subtly different 1980s bikes. Generate bodies, wardrobe and surroundings. Friend1 brown wide-collar shirt, patterned red collar and cuffs, white flared trousers, black shoes, lightly tinted aviators. Friend2: mustard wide-collar shirt, dark flared trousers. Friend3: muted blue wide-collar shirt, cream trousers. They are joyful close friends; each keeps his assigned bike. 0.0-1.2s — Full-body roadside tripod shot. First frame: Friend1centered beside parked bike1. He steps toward its handlebars; wind moves his shirt. Hard cut. 1.2-3.6s — Tight oblique close-up, handheld beside bike1: Friend1 red-patterned cuff and hand bring a metal key into view. Follow the key into the bike's actual ignition position; he inserts and turns it. Preserve the reference bike's layout. Hard cut. 3.6-5.8s — Medium side view, low tripod: Friend1 settles astride bike1 and drives the kick-start lever downward with his foot. The engine catches, metal trembles, suspension compresses; his hands settle on the grips. Hard cut. 5.8-11.0s — One uninterrupted front-facing tracking shot from a lead vehicle, camera 1.1m high, initially 5m ahead. Friend1 is already riding and singing, centered. Gradually widen to an 84-degree diagonal field of view and pull 8m ahead to accommodate three bikes. At 7.0s Friend2 visibly advances from the distant background on SCREEN-LEFT, closes the gap on bike2 and matches Friend1 speed alongside him. At 9.0s Friend3 similarly advances from behind on SCREEN-RIGHT on bike3 and draws parallel. The approaches are continuous, wheels turning against the road. By 10s all three ride abreast, about 1.5m between handlebars: Friend2 LEFT, Friend1 CENTER, Friend3 RIGHT. They sing together, exchange brief smiles and keep looking back to the road. Friend1 remains the visual anchor. Hard cut. 11.0-12.0s — Rider-view macro of bike1's round analog speedometer: legible km/h scale, needle pointing to the marked 80, slight engine vibration. Hard cut. 12.0-13.0s — Low side-mounted close-up of bike1's spinning front tyre: compressed contact patch, spokes blurred by rotation, asphalt streaming backward. Hard cut. 13.0-14.0s — Low side tracking angle on Friend1 boot, engine and fuel tank, suspension responding to the road. Hard cut. 14.0-15.0s — Wide frontal tracking view: the same left-center-right formation, three distinct friends singing, Friend1 centered, road receding behind them. Camera and grade: physical vehicle-mounted motion, restrained vibration, natural blur. Rich 1980s color-negative film: warm browns, vivid greens, sky blue, natural skin; soft overcast daylight from camera-left, gentle halation on chrome, fine grain, subtle gate weave and occasional faint scratches. Colorful photographed reality rather than sepia, glossy CGI or heavy VHS damage. Audio: cheerful original "la-la-la" male singing; each friend joins on arrival. Lip-sync follows the singing, continuing over inserts. Vintage engine notes, kick-start clack, wind and tyre hiss. No subtitles. Continuity: exactly three friends and three assigned bikes total; one rider per bike. Initial opening shows Abhishek alone. Hands retain steering control during riding. Distinct faces, unchanged clothing and bike geometry. Count of modern vehicles, digital dashboards, phones, overlays and watermarks: zero.”
Now hit generate button and wait 2 min
Boom you will get amazing 80’s style video
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Photo Prompt ——
Use my uploaded face photo as the identity reference and the provided reference image as the exact visual/composition reference. Create an ultra-realistic 1980s vintage portrait of me. Keep my facial identity 100% consistent with my uploaded face photo — preserve my natural face shape, skin tone, eyes, eyebrows, nose, lips, jawline, beard/facial hair, and natural facial proportions. Do not beautify, reshape, slim, age, or alter my face. Recreate the reference image as closely as possible: I am seated in a relaxed vintage chair, leaning slightly back, with my legs crossed exactly like the reference. One elbow rests naturally on the chair arm while my hand is raised under my chin, with fingers relaxed. Keep the same head angle, body posture, hand placement, leg position, camera angle, close-to-medium full-body framing, and overall composition. Clothing must closely match the reference: a colorful retro 1980s windbreaker jacket in teal/blue, purple, and magenta color-block panels, worn open over a plain cream/off-white knitted sweater. Add a thin silver chain necklace, light-wash heavily stone-washed/faded high-waisted jeans, white crew socks, and clean white retro sneakers. Include the same vintage digital wristwatch. Keep the relaxed oversized 80s fashion silhouette. Give me an authentic 1980s men's hairstyle — thick, dense, voluminous dark hair with natural waves/curls, rounded fluffy volume on top, slightly longer sides and back, neatly styled with a subtle healthy shine. No modern fade, undercut, buzz cut, or contemporary hairstyle. Recreate the retro interior/background: a dark vintage lounge chair, indoor tropical plant on the left, and a nostalgic 1980s colorful diagonal neon/light-striped backdrop in blue, pink, and purple tones. Include a vintage Sony-style cassette/boombox beside the chair. Maintain the same placement and depth of the background elements. Make the image look like a genuine photograph taken in the 1980s, not a modern photograph with a vintage filter. Use warm analog film tones, slightly faded colors, soft contrast, gentle highlights, subtle 35mm film grain, realistic skin pores and texture, mild lens softness, natural shadows, slight color imperfections, dust, scratches, faded corners, and an authentic worn vintage photo border. Important: My uploaded face photo controls ONLY my facial identity. The reference image controls the pose, clothing, hairstyle, body positioning, background, props, composition, camera perspective, lighting, and overall 1980s aesthetic. Do not copy the reference person's facial identity. Ultra-realistic, photorealistic, authentic 1980s fashion photography, natural anatomy, realistic hands, realistic fabric textures, cinematic vintage lighting, detailed but not digitally oversharpened, vertical 9:16 portrait.”
Now hit generate button
You will get a 80’s style photo
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