from fastapi import FastAPI, File, UploadFile, Form, Body from fastapi.responses import StreamingResponse from fastapi.middleware.cors import CORSMiddleware from typing import List import io from PIL import Image, ImageOps import numpy as np import compColors import dominantColors import recolorReinhardAlgo import recolorOTAlgo import recolorTransferAlgo import recolorLumaConverterAlgo import recolorPaletteBasedTransfer import recolorReinhardV2Algo import recolorLinearColorTransfer import recolorStrictTransfer import matchCollection import ColorReplacer import ColorMask from typing import Optional import random app = FastAPI() app.add_middleware( CORSMiddleware, allow_origins=["*"], allow_credentials=True, allow_methods=["*"], allow_headers=["*"], ) @app.post("/dominantColor") async def dominant_color(file: UploadFile = File(...), num_colors: int = Form(...), ordered: bool = Form(False)): """ Receive an image file and an integer and return the dominant color(s). """ print('num_colors: ', num_colors) file_content = await file.read() image_bytes = io.BytesIO(file_content) im = Image.open(image_bytes) dominantColorsRGB = dominantColors.findDominantColors(image_bytes, num_colors, False) dominantColorsHex = [dominantColors.rgb_to_hex(color) for color in dominantColorsRGB] return {"dominantColors": dominantColorsHex} @app.post("/ColorPalettes/") async def color_palettes(colors: str = Form(...)): """ Receive an array of strings representing colors and return a color palette based on these colors. """ #maybe this isn't necessary. converting the string to an array of strings colors = [color.strip() for color in colors.split(',')] #generate the first pallete, which is the complementary colors of the given colors complementaryColors = [] for color in colors: complementaryColors.append(compColors.complementary_colors(color)) #generate the second palette using the adjacent colors algorithm: adjacentColors = [] for color in colors: _adjcolors = compColors.adjacent_colors(color) for _color in _adjcolors: if _color not in adjacentColors: adjacentColors.append(_color) #generate the third palette using the gradient colors algorithm: gradientColors = [] for i in range(len(colors)-1): gradientColors.append(compColors.gradient_colors(colors[i], colors[i+1])) #Fixing size of palletes to 5 colors: complementaryColors = [complementaryColors[i:i + 5] for i in range(0, len(complementaryColors), 5)] adjacentColors = [adjacentColors[i:i + 5] for i in range(0, len(adjacentColors), 5)] colors = [colors[i:i + 5] for i in range(0, len(colors), 5)] return {"inputColor": colors, "complementaryColors": complementaryColors, "adjacentColors": adjacentColors, "gradientColors": gradientColors} @app.post("/recolor/") async def recolor(file: UploadFile = File(...), colors: str = Form(...), new_colors: str = Form(...), random_colors: bool = Form(False), model: str = Form(...), mask: Optional[UploadFile] = File(None)): """ Receive an image file and an array of strings representing colors of a selected pallete and recolor an image. """ method = model invertColors = False colors = [color.strip() for color in colors.split(',')] new_colors = [new_color.strip() for new_color in new_colors.split(',')] file_content = await file.read() image_bytes = io.BytesIO(file_content) image = Image.open(image_bytes) if invertColors: image = ImageOps.invert(image) image_np = np.array(image) if method == "CCA": print('CCA generated') #Characteristic Color Analysis recolorReinhardAlgo.recolor(image_np, colors) elif method == "OTA": print('OTA generated') #Optimal Transport Algorithm transfer recolorOTAlgo.recolor(image_np, colors) elif method =="KMEANS": print('KMEANS generated') #K-means clustering transfer recolorTransferAlgo.recolor(image_np, colors) elif method == "LUMA": print('Luma generated') #Luma converter transfer recolorLumaConverterAlgo.remap_image_colors(image_np, colors) elif method == "palette": #palette transfer print('palette generated') recolorPaletteBasedTransfer.recolor(image_np, colors) elif method == "Reinhardv2": print('Reinhardv2 generated') recolorReinhardV2Algo.recolor(image_np, colors) elif method == "LinearColorTransfer": print('LinearColorTransfer generated') recolorLinearColorTransfer.recolor(image_np, colors) elif method == "StrictTransfer": print('StrictTransfer started') if random_colors: random.shuffle(new_colors) recolorStrictTransfer.recolor(image_np, colors, new_colors) elif method == "ColorMask": print('ColorMask started') ColorMask.create_mask(image_np, colors[0]) #mask image: if mask is not None: mask_content = await mask.read() mask_image = Image.open(io.BytesIO(mask_content)) # Ensure mask_image is the same size as result_image result_image = Image.open('./result.jpg') result_np = np.array(result_image) print('result_np', result_np.size) print('image_np', image_np.size) if mask_image.size != result_image.size: mask_image = mask_image.resize(result_image.size) mask_image = mask_image.convert('RGB') mask_np = np.array(mask_image) # Create a new image array based on the mask new_image_np = np.where(mask_np == 0, result_np, image_np) # Save the new image new_image = Image.fromarray(new_image_np) new_image.save('./result.jpg') img_file = open("./result.jpg", "rb") return StreamingResponse(img_file, media_type="image/jpeg") # @app.post("/collection/") # async def create_collection(collection: str = Body(...), colors: List[str] = Body(...)): # """ # Endpoint to create a collection with items. # """ # result = matchCollection.predict_palette(collection, colors[0]) # print(result) # #preparar o dado pra ser respondido # return {"collection": result} @app.post("/collection/") async def create_collection(collection: str = Body(...), colors: List[str] = Body(...)): """ Endpoint to create a collection with items. """ palettes = [matchCollection.predict_palette(collection, color) for color in colors] return {"collection": collection, "palettes": palettes} @app.get("/test/") async def test(): """ Test endpoint to check if the server is running. """ return {"message": "Server is running!"} if __name__ == "__main__": import uvicorn print("Server is running") uvicorn.run(app, host="0.0.0.0", port=7860) #how to run: #source env/bin/activate #uvicorn server:app --reload #curl -X POST http://0.0.0.0:4201/collection/ \ -H "Content-Type: application/json" \ -d '{"collection": "FLORAL", "colors": ["#1f3b4a", "#597375", "#7f623e", "#5c453c"]}'