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question:As a prompt generator for a generative AI called "Midjourney", you will create image prompts for the AI to visualize. I will give you a concept, and you will provide a detailed prompt for Midjourney AI to generate an image. Please adhere to the structure and formatting below, and follow these guidelines: Do not use the words "description" or ":" in any form. Do not place a comma between [ar] and [v]. Write each prompt in one line without using return. Structure: [1] = 一个在试衣间的女孩 [2] = a detailed description of [1] with specific imagery details. [3] = a detailed description of the scene's environment. [4] = a detailed description of the compositions. [5] = a detailed description of the scene's mood, feelings, and atmosphere. [6] = A style (e.g. photography, painting, illustration, sculpture, artwork, paperwork, 3D, etc.) for [1]. [7] = a detailed description of the scene's mood, feelings, and atmosphere. [ar] = Use "--ar 16:9" for horizontal images, "--ar 9:16" for vertical images, or "--ar 1:1" for square images. [v] = Use "--niji" for Japanese art style, or "--v 5" for other styles. Formatting: Follow this prompt structure: "/imagine prompt: [1], [2], [3], [4], [5], [6], [7], [ar] [v]". Your task: Create 4 distinct prompts for each concept [1], varying in details description, environment,compositions,atmosphere, and realization. Write your prompts in english. Do not describe unreal concepts as "real" or "photographic". Include one realistic photographic style prompt with lens type and size. Separate different prompts with two new lines. Example Prompts: /imagine prompt: cute dog, fluffy fur, wagging tail, playful expression, sitting on a grassy field, under a clear blue sky, with a colorful collar, in a natural and vibrant setting, by a lake, captured with a Nikon D750 camera, 50mm lens, shallow depth of field, composition focused on the dog's face, capturing its joyful spirit, in a style reminiscent of William Wegman's iconic dog portraits. --ar 1:1 --v 5.2 /imagine prompt: beautiful women in the coffee shop, elegant and sophisticated, sipping a cup of steaming coffee, natural sunlight streaming through the window, soft and warm color tones, vintage decor with cozy armchairs and wooden tables, a bookshelf filled with classic novels, delicate porcelain teacups, a hint of aromatic coffee beans in the air, captured by a Leica M10 camera, 35mm lens, capturing the essence of timeless beauty, composition focused on the woman's face and hands, reminiscent of a painting by Leonardo da Vinci. --ar 1:1 --v 5.2 /imagine prompt: A captivating Halo Reach landscape with a Spartan amidst a battlefield, fallen enemies around, smoke and fire in the background, emphasizing the Spartan's determination and bravery, detailed environment blending chaos and beauty, Illustration, digital art, --ar 16:9 --v 5
answer:/imagine prompt: a young woman trying on a glamorous evening gown, shimmering fabric with intricate beading and embroidery, standing in front of a full-length mirror, surrounded by soft glowing lights, makeup brushes and cosmetics scattered on a vanity table, a luxurious dressing room with elegant chandeliers and plush carpets, captured with a Canon EOS 5D Mark IV camera, 85mm lens, focusing on the dress details and the woman's reflection, evoking a sense of anticipation and glamour, in a style reminiscent of fashion photography. --ar 9:16 --v 5 /imagine prompt: a teenage girl in a bohemian clothing store, wearing a flowy floral maxi dress, colorful tapestries and eclectic decor hanging on the walls, racks of vintage and handmade accessories, incense burning releasing a warm and earthy scent, natural sunlight filtering through sheer curtains, a cozy and welcoming atmosphere with a hint of mystery, captured with a Fujifilm X-T3 camera, 35mm lens, emphasizing the girl's free-spirited expression and the unique fashion pieces, in a style resembling a whimsical illustration. --ar 16:9 --v 5 /imagine prompt: a bride in a rustic barn wedding venue, wearing a lace wedding dress with a delicate veil, standing under a floral arbor adorned with wildflowers and greenery, wooden beams and fairy lights creating a romantic ambiance, soft golden hour sunlight casting a warm glow, hay bales and vintage wooden barrels adding a rustic charm, captured with a Sony A7III camera, 50mm lens, focusing on the bride's radiant smile and the natural beauty of the setting, conveying a sense of love and bliss, in a style reminiscent of documentary photography. --ar 16:9 --v 5 /imagine prompt: a young ballerina in a sunlit dance studio, wearing a pastel tutu and pointe shoes, gracefully executing a pirouette with her arms outstretched, mirrored walls reflecting her fluid movements, ballet barres and soft pink mats enhancing the ethereal atmosphere, gentle piano music filling the space, captured with a Nikon Z6 camera, 24mm lens, capturing the dancer's elegance and precision, with a focus on her poise and form, evoking a sense of grace and beauty, in a style inspired by classical paintings. --ar 9:16 --v 5.2
question:how can I get just shop polygons from the overpass api
answer:You can query the Overpass API to retrieve only shop polygons by specifying the relevant tags in your query. Here is an example query that retrieves all shop polygons: ```xml <osm-script output="json"> <query type="way"> <has-kv k="shop"/> <bbox-query {{bbox}}/> </query> <print mode="body"/> </osm-script> ``` In this query, we are filtering for ways with the tag "shop" and then specifying a bounding box to narrow down the search area. This will return all shop polygons within the given bounding box. You can further customize the query by adding more specific shop tags (e.g. "shop=supermarket", "shop=pharmacy", etc.) to only retrieve certain types of shops. You can also adjust the bounding box to focus on a specific area. You can run this query using the Overpass Turbo application (https://overpass-turbo.eu/) or directly through the Overpass API. Simply replace `{{bbox}}` with the desired bounding box coordinates in the query.
question:how would that query look for Overpass Turbo
answer:In Overpass Turbo, you can directly input the following query to retrieve all shop polygons: ``` /* This has been generated by the overpass-turbo wizard. The original search was: “shop=*” */ [out:json][timeout:25]; // fetch area “{{bbox}}” to search in {{geocodeArea:World}}; // gather results ( way["shop"]({{bbox}}); ); // print results out body; >; out skel qt; ``` Simply copy and paste this query into the query box on the Overpass Turbo website, adjust the bounding box if needed, and then run the query to retrieve the shop polygons data. This query will return all shop polygons within the specified bounding box.
question:how can I get park polygons
answer:To retrieve park polygons from the Overpass API, you can query for areas that have the specific tag associated with parks. Here is an example query that you can use to get park polygons: ```xml <osm-script output="json"> <query type="way"> <has-kv k="leisure" v="park"/> <bbox-query {{bbox}}/> </query> <print mode="body"/> </osm-script> ``` In this query, we are filtering for ways with the tag "leisure=park" to specifically target park areas. You can further adjust the query by specifying a bounding box to focus on a particular area. You can run this query using the Overpass Turbo interface by replacing `{{bbox}}` with the desired bounding box coordinates and then executing the query to retrieve park polygons data. This query will return park polygons within the specified bounding box that have the leisure=park tag.