import os, sys, json, re, time, base64, random, shutil import gradio as gr import numpy as np import requests from requests import Session from requests.adapters import HTTPAdapter from requests.packages.urllib3.util.retry import Retry from datetime import datetime import urllib.parse from groq import Groq from exif import Image from PIL import Image as PILImage, ExifTags as PILExifTags from io import BytesIO import colorsys import spaces if not "SPACE" in os.environ: from dotenv import load_dotenv load_dotenv() # MARK: INIT MAX_SEED = np.iinfo(np.int32).max MAX_IMAGE_SIZE = 2048 GROQ_APIKEY_PROMPTENHANCE = os.getenv("GROQ_APIKEY_PROMPTENHANCE") API1 = urllib.parse.unquote(os.getenv("API1")) API2 = os.getenv("API2") API2_MODELS = urllib.parse.unquote(API2 + "/models") API2_IMAGE = urllib.parse.unquote(API2 + "/imagine") CACHE_DIR = os.path.join(os.path.dirname(__file__), "cache") IMAGE_DIR = "cache/images/" if not os.path.exists(CACHE_DIR): os.makedirs(CACHE_DIR) print(f"Created cache dir on path {CACHE_DIR}") os.makedirs(os.path.join(CACHE_DIR, "images")) print(f"Created images dir on path {IMAGE_DIR}") RES = os.path.join(os.path.dirname(__file__), "_res") gr.set_static_paths(paths=["_res/", "_res/assets/", "_res/assets/emojis/", "_res/assets/favicons/", IMAGE_DIR]) custom_css = RES + "/_custom.css" custom_js = RES + "/_custom.js" custom_head = f""" """ theme = gr.themes.Soft( # primary_hue="orange", radius_size="sm", neutral_hue=gr.themes.Color( c100="#a6adc8", c200="#9399b2", c300="#7f849c", c400="#6c7086", c50="#cdd6f4", c500="#585b70", c600="#45475a", c700="#313244", c800="#1e1e2e", c900="#181825", c950="#11111b", ), ) title = "Bilder Builder" # MARK: READ EXIF def read_exif(image_path): with open(image_path, "rb") as src: img = Image(src) img_comment = json.loads(img.user_comment) # checking if the key exists before removing if "concept" in img_comment: img_comment.pop("concept") return img_comment def read_image_exfi_data(image_path): print("Imagepath:", image_path) img_exif_make, img_exif_comment = read_exif(image_path) return None, image_path, img_exif_comment # MARK: GROQ PROMPT ENHANCE def groq_enhance_process(Prompt=""): client = Groq(api_key=GROQ_APIKEY_PROMPTENHANCE) Prompt = "random prompt" if Prompt == "" else Prompt SYSTEMPROMPT = os.path.join(RES, "groq_systemmessage_prompt_enhance.json") with open(SYSTEMPROMPT, "r") as f: SYSTEMPROMPT = json.load(f) completion = client.chat.completions.create( model="llama-3.1-70b-versatile", messages=[SYSTEMPROMPT, {"role": "user", "content": Prompt}], temperature=0.8, max_tokens=512, top_p=0.9, stream=False, seed=random.randint(0, MAX_SEED), stop=None, ) if completion.choices[0].message.content != "": enhanced_prompt = completion.choices[0].message.content enhanced_prompt = re.sub(r"[\.\"]+", "", enhanced_prompt) return enhanced_prompt def image_get_size(image_path): img = PILImage.open(image_path) # print("Image size:", img.size) width, height = img.size return width, height # MARK: DOMINANT COLOR def image_get_dominant_color(image_path): img = PILImage.open(image_path) img = img.convert("RGB") img = img.resize((100, 100), resample=0) pixels = list(img.getdata()) # Erzeuge eine Liste mit den Häufigkeiten der Farben colors = [] for pixel in pixels: r, g, b = pixel h, s, v = colorsys.rgb_to_hsv(r / 255, g / 255, b / 255) if v > 0.5: # Filteriere hellere Farben aus continue if v > 0.99: # Filteriere Weiß aus continue colors.append((h, s, v)) # Ermittle die dominante Farbe dominant_color = max(colors, key=lambda x: x[2]) dominant_color_rgb = colorsys.hsv_to_rgb(dominant_color[0], dominant_color[1], dominant_color[2]) dominant_color_rgb = [int(c * 255) for c in dominant_color_rgb] dominant_color_rgb = f"rgb({dominant_color_rgb[0]}, {dominant_color_rgb[1]}, {dominant_color_rgb[2]})" # print(dominant_color_rgb) return dominant_color_rgb # MARK: CLEAR COMPONENTS def clear_components(): return None def process(Prompt, used_model, image_width, image_height, image_ratio, image_seed, randomize_seed, gallery): if Prompt == "": gr.Info("Kein Prompt angegeben, es wird ein zufälliger Prompt generiert.", duration=12) Prompt = groq_enhance_process("random prompt") image_ratio = "9:16" if image_ratio == "" else image_ratio used_seed = random.randint(0, MAX_SEED) if image_seed == 0 or randomize_seed else image_seed # used_model = "turbo" if int(image_width) > 1024 or int(image_height) > 1024 else "flux" # turbo, flux timestamp = datetime.now().strftime("%Y-%m-%d-%H-%M-%S") filename_prompt = re.sub(r"[^\w\s-]", "", Prompt).strip().replace(" ", "_") filename = timestamp + "_" + filename_prompt[:100] + ".png" file_path = IMAGE_DIR + filename # Retry-Logik mit requests und Retry session = Session() retries = Retry( total=3, status_forcelist=[429, 500, 502, 503, 504], backoff_factor=0.3, respect_retry_after_header=True ) # Max 3 Versuche # Codes, die wiederholt werden # Exponential Backoff # Retry-Header beachten adapter = HTTPAdapter(max_retries=retries) session.mount("https://", adapter) session.mount("http://", adapter) u_model = re.sub("api\d-", "", used_model.lower()) API1_REQUEST_URL = f"{API1}{urllib.parse.quote(Prompt)}?model={u_model}&width={image_width}&height={image_height}&nologo=true&enhance=false&nofeed=true&seed={used_seed}" API2_REQUEST_URL = f"{API2_IMAGE}?prompt={urllib.parse.quote(Prompt)}&size={urllib.parse.quote(image_ratio)}&seed={used_seed}&model={u_model}" REQUEST_URL = API1_REQUEST_URL if used_model.lower().startswith("api1-") else API2_REQUEST_URL print("REQUEST URL:\n" + REQUEST_URL + "\n\nImagine API Request started") try: response = session.get(REQUEST_URL, timeout=60) if response.status_code == 200: print("REQUEST URL:\n" + REQUEST_URL + "\n\nImagine API Request solved") img = PILImage.open(BytesIO(response.content)) img.save(file_path, "png") print("Save image to: ") print(file_path) # img_exif_comment = "" # read_exif(file_path) img_dominant_color = image_get_dominant_color(file_path) img_width, img_height = image_get_size(file_path) new_gallery = [i for i in gallery] if gallery else [] new_gallery.append(file_path) gallery = new_gallery return ( {"value": Prompt, "__type__": "update"}, {"value": file_path, "__type__": "update"}, {"value": gallery, "selected_index": len(gallery) - 1, "__type__": "update"}, {"value": None, "visible": False, "__type__": "update"}, {"visible": True, "__type__": "update"}, {"value": Prompt, "visible": True, "__type__": "update"}, img_width, img_height, used_seed, {"value": file_path, "visible": True, "__type__": "update"}, img_dominant_color, used_seed, ) else: print("Imagine API Request ERROR") raise gr.Error("Imagine API-Aufruf fehlgeschlagen 💥!", duration=15) except requests.exceptions.Timeout: raise gr.Error("⏰ Zeitüberschreitung beim API-Aufruf", duration=15) except requests.exceptions.RequestException as e: print(f"Unbekannter Fehler beim API-Aufruf: {e}") raise gr.Error("Unbekannter Fehler beim API-Aufruf! 🤷‍♂️", duration=15) def check_api(url): try: response = requests.get(url, timeout=8) print(f"Checking Status for: {url}, it returns statuscode {response.status_code}") return response.status_code except requests.exceptions.RequestException as e: print(f"An error occurred: {e}") return int(999) def get_inference_models(): status_api_1 = check_api(API1) status_api_2 = check_api(API2) info_api_1 = "🟢API1👍" if status_api_1 == 200 else "🔴API1👎🔌" info_api_2 = "🟢API2👍" if status_api_2 == 200 else "🔴API2👎🔌" api_models_1 = ["API1-FLUX", "API1-FLUX-Pro", "API1-FLUX-CablyAI", "API1-Turbo"] api_models_2 = ["API2-FLUX-Realism", "API2-FLUX-Pixel", "API2-FLUX-Anime", "API2-FLUX-3D", "API2-FLUX-Disney", "API2-ANY-DARK"] models = [model for model in api_models_1 if status_api_1 == 200] + [model for model in api_models_2 if status_api_2 == 200] info_api_status = f"Status: {info_api_1} & {info_api_2}" return gr.update(choices=models, value=models[0], interactive=True, info=info_api_status) # MARK: Gradio BLOCKS UI with gr.Blocks(theme=theme, head=custom_head, css=custom_css, js=custom_js, title=title) as demo: with gr.Row(elem_classes="row-header"): gr.Markdown( f"""

{title}

Aktuell funktioniert die APP nicht, da ich heute wenig Zeit habe werde ich es erst morgen schaffen die Probleme zu beheben.

LG Sebastian gib dem Space gerne ein

""", elem_classes="md-header", ) with gr.Tab("Bilder Builder"): with gr.Row(): with gr.Column(scale=2): # min_width=420, with gr.Row(): placeholder_text = "[???] Generiert dir einen zufälligen Prompt.\n[STERN] optimiert deinen eignen Prompt.\n[RUN] generiert dein Bild." text_prompt = gr.Textbox( label="Prompt", show_label=False, lines=12, max_lines=18, placeholder=placeholder_text, elem_id="prompt_input", elem_classes="prompt-input hide-progress", autofocus=True, ) with gr.Row(): random_prompt_button = gr.Button("", variant="secondary", elem_id="random_prompt_btn", elem_classes="random-prompt-btn", icon="_res/assets/star_light_48.png") enhance_prompt_button = gr.Button( "", variant="secondary", elem_id="enhance_prompt_btn", elem_classes="enhance-prompt-btn", icon="_res/assets/star_light_48.png" ) run_button = gr.Button("Erstellen", variant="primary", elem_id="run_btn", elem_classes="run-btn", interactive=False) with gr.Row(elem_classes="image_size_selctor_wrapper"): with gr.Column(scale=1): with gr.Row(): # inference_models, selected_model = get_inference_models() # select_model = gr.Dropdown(choices=inference_models, value=selected_model, label="Model", elem_id="select_model", elem_classes="select-model") select_model = gr.Dropdown(label="Model", elem_id="select_model", elem_classes="select-model") # with gr.Row(): image_width = gr.Number( label="Breite", minimum=256, maximum=MAX_IMAGE_SIZE, value=576, step=32, elem_id="image_width_selector", elem_classes="image-width-selector", scale=1, visible=False, ) image_height = gr.Number( label="Höhe", minimum=256, maximum=MAX_IMAGE_SIZE, value=1024, step=32, elem_id="image_height_selector", elem_classes="image-height-selector", scale=1, visible=False, ) with gr.Row(): image_ratio_buttons = gr.Radio( ["9:16", "3:4", "2:3", "1:1"], value="9:16", label="Hochformat", show_label=True, info="Seitenverhältniss drehen", interactive=True, elem_id="image_ratio_buttons", elem_classes="image-ratio-buttons", container=True, scale=2, ) switch_width_height = gr.Button("", size="sm", elem_id="switch_width_height", elem_classes="switch-ratio-btn", variant="primary", scale=1) with gr.Column(): randomize_seed = gr.Checkbox(label="Randomize seed", value=True, elem_classes="random-seed-cb toggle-btn") image_seed = gr.Slider( label="Seed", info="Jeder Seed generiert ein anderes Bild mit dem selben Prompt", minimum=0, step=1, value=42, maximum=MAX_SEED, elem_id="image_seed", elem_classes="image-seed hide-progress", interactive=False, ) with gr.Column(scale=4): # min_width=600, with gr.Row(): with gr.Column(scale=1): with gr.Row(): with gr.Column(): output_image = gr.Image( show_label=False, min_width=320, elem_id="output_image", elem_classes="output-image", type="filepath", format="webp", visible=False ) gallery = gr.Gallery( label="Bisher erstellte Bilder", show_label=True, elem_id="gallery", columns=[4], object_fit="cover", height="auto", interactive=False, type="filepath", format="webp", ) with gr.Column(scale=1, visible=False, elem_classes="image-info-wrapper") as image_info_wrapper: with gr.Group(): image_informations = gr.Markdown("""## Bildinformationen""", visible=True) with gr.Row(elem_classes="img-size-wrapper"): image_info_tb_width = gr.Textbox( label="Breite", lines=1, max_lines=1, interactive=False, show_copy_button=True, elem_classes="image-info-tb-width" ) image_info_tb_height = gr.Textbox( label="Höhe", lines=1, max_lines=1, interactive=False, show_copy_button=True, elem_classes="image-info-tb-height" ) with gr.Row(elem_classes="img-seed-wrapper"): image_info_tb_seed = gr.Textbox(label="Seed", lines=1, max_lines=1, interactive=False, show_copy_button=True, elem_classes="image-info-tb-seed") image_info_tb_prompt = gr.Textbox( "Bild Prompt", lines=4, max_lines=8, interactive=False, elem_classes="hide-progress", show_copy_button=True, visible=False ) image_download_button = gr.DownloadButton("Bild herunterladen", value=None, elem_classes="download-button", variant="primary", visible=False) output_url = gr.Textbox(label="Output URL", show_label=True, interactive=False, visible=False) outpu_image_comment = gr.Json(visible=False) output_dominant_image_color = gr.Textbox(show_label=False, elem_id="dominant_image_color", visible=True, elem_classes="output-dominant-image-color") demo.load( lambda x: ({"interactive": False, "__type__": "update"}, {"interactive": False, "__type__": "update"}, {"interactive": False, "__type__": "update"}), outputs=[run_button, enhance_prompt_button, random_prompt_button], ).then(get_inference_models, outputs=[select_model]).then( lambda x: ({"interactive": True, "__type__": "update"}, {"interactive": True, "__type__": "update"}, {"interactive": True, "__type__": "update"}), outputs=[run_button, enhance_prompt_button, random_prompt_button], ) def switch_image_size_values(image_width, image_height): return image_height, image_width def switch_image_ratio_buttons(ratio_value): ratio_value = ratio_value.split(":") ratio_value_new = f"{int(ratio_value[1])}:{int(ratio_value[0])}" if int(ratio_value[1]) > int(ratio_value[0]): # Querformat new_choises = ["16:9", "4:3", "3:2", "1:1"] new_label = "Querformat" elif int(ratio_value[1]) < int(ratio_value[0]): # Hochformat new_choises = ["9:16", "3:4", "2:3", "1:1"] new_label = "Hochformat" elif int(ratio_value[1]) == int(ratio_value[0]): new_choises = image_ratio_buttons.choices new_label = "Quadratisch" return {"choices": new_choises, "value": ratio_value_new, "label": new_label, "__type__": "update"} def calculate_ratio_values(image_ratio_buttons): ratio_value = image_ratio_buttons.split(":") if int(ratio_value[0]) > int(ratio_value[1]): a = 1024 b = int(a * int(ratio_value[1]) / int(ratio_value[0])) b = round(b / 8) * 8 new_width = a new_height = b new_label = "Querformat" elif int(ratio_value[0]) < int(ratio_value[1]): b = 1024 a = int(b * int(ratio_value[0]) / int(ratio_value[1])) a = round(a / 8) * 8 new_width = a new_height = b new_label = "Hochformat" elif int(ratio_value[0]) == int(ratio_value[1]): new_width = 1024 new_height = 1024 new_label = "Quadratisch" return {"label": new_label, "__type__": "update"}, new_width, new_height switch_width_height.click(fn=switch_image_size_values, inputs=[image_width, image_height], outputs=[image_width, image_height], show_progress="hidden", show_api=False) switch_width_height.click(fn=switch_image_ratio_buttons, inputs=[image_ratio_buttons], outputs=[image_ratio_buttons], show_progress="hidden", show_api=False) image_ratio_buttons.input( fn=calculate_ratio_values, inputs=[image_ratio_buttons], outputs=[image_ratio_buttons, image_width, image_height], show_progress="hidden", show_api=False ) run_button.click( fn=lambda: ({"interactive": False, "__type__": "update"}, {"interactive": False, "__type__": "update"}, {"interactive": False, "__type__": "update"}), outputs=[run_button, enhance_prompt_button, random_prompt_button], show_api=False, js="() => document.querySelector('dotlottie-player').play()", ).then(fn=clear_components, outputs=[output_image], show_api=False).then( fn=process, inputs=[text_prompt, select_model, image_width, image_height, image_ratio_buttons, image_seed, randomize_seed, gallery], outputs=[ text_prompt, output_image, gallery, output_url, image_informations, image_info_tb_prompt, image_info_tb_width, image_info_tb_height, image_info_tb_seed, image_download_button, output_dominant_image_color, image_seed, ], ).then( fn=lambda: ({"interactive": True, "__type__": "update"}, {"interactive": True, "__type__": "update"}, {"interactive": True, "__type__": "update"}), outputs=[run_button, enhance_prompt_button, random_prompt_button], show_api=False, js="() => document.querySelector('dotlottie-player').stop()", ) randomize_seed.input(lambda x: {"interactive": False if x == True else True, "__type__": "update"}, inputs=[randomize_seed], outputs=[image_seed], show_api=False) enhance_prompt_button.click(fn=groq_enhance_process, inputs=[text_prompt], outputs=[text_prompt], show_api=False) random_prompt_button.click(fn=groq_enhance_process, inputs=None, outputs=[text_prompt], show_api=False) # MARK: Gradio LAUNCH demo.launch(show_api=True)