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You need to be a Pro Member in Colab 'else' You will face Malloc() Issues [ Less Memory Issue ]

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  1. Flux-RealPix.ipynb +446 -0
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+ "nbformat_minor": 0,
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+ "metadata": {
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+ "colab": {
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+ "provenance": [],
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+ "gpuType": "T4"
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+ },
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+ "kernelspec": {
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+ "name": "python3",
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+ "display_name": "Python 3"
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+ },
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+ "language_info": {
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+ "name": "python"
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+ },
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+ "accelerator": "GPU"
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+ },
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+ "cells": [
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+ {
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+ "cell_type": "code",
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+ "execution_count": 1,
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+ "metadata": {
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+ "colab": {
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+ "base_uri": "https://localhost:8080/"
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+ },
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+ "id": "L1CPm6HAZuTg",
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+ "outputId": "3a85cb03-b18f-4e5b-8c5f-2f577bc46598"
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+ },
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+ "outputs": [
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+ {
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+ "output_type": "stream",
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+ "name": "stdout",
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+ "text": [
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+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m71.4/71.4 kB\u001b[0m \u001b[31m5.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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+ "\u001b[?25hDownloading websockets-12.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (130 kB)\n",
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+ "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m130.2/130.2 kB\u001b[0m \u001b[31m11.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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+ "\u001b[?25hInstalling collected packages: pydub, websockets, tomlkit, semantic-version, ruff, python-multipart, orjson, h11, ffmpy, aiofiles, uvicorn, starlette, httpcore, httpx, fastapi, diffusers, gradio-client, peft, gradio, spaces\n",
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+ " Attempting uninstall: tomlkit\n",
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+ " Found existing installation: tomlkit 0.13.2\n",
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+ " Uninstalling tomlkit-0.13.2:\n",
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+ " Successfully uninstalled tomlkit-0.13.2\n",
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+ "Successfully installed aiofiles-23.2.1 diffusers-0.30.2 fastapi-0.112.4 ffmpy-0.4.0 gradio-4.43.0 gradio-client-1.3.0 h11-0.14.0 httpcore-1.0.5 httpx-0.27.2 orjson-3.10.7 peft-0.12.0 pydub-0.25.1 python-multipart-0.0.9 ruff-0.6.4 semantic-version-2.10.0 spaces-0.30.2 starlette-0.38.5 tomlkit-0.12.0 uvicorn-0.30.6 websockets-12.0\n"
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+ ]
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+ }
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+ ],
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+ "source": [
172
+ "!pip install torch diffusers spaces transformers peft sentencepiece gradio"
173
+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "source": [
178
+ "# Authenticate with Hugging Face\n",
179
+ "from huggingface_hub import login\n",
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+ "\n",
181
+ "# Log in to Hugging Face using the provided token\n",
182
+ "hf_token = 'hf-token-authentication'\n",
183
+ "login(hf_token)"
184
+ ],
185
+ "metadata": {
186
+ "colab": {
187
+ "base_uri": "https://localhost:8080/"
188
+ },
189
+ "id": "1Q39l67NZ4F-",
190
+ "outputId": "d5c36fff-c230-4101-917b-8bb13a717d40"
191
+ },
192
+ "execution_count": 2,
193
+ "outputs": [
194
+ {
195
+ "output_type": "stream",
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+ "name": "stdout",
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+ "text": [
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+ "The token has not been saved to the git credentials helper. Pass `add_to_git_credential=True` in this function directly or `--add-to-git-credential` if using via `huggingface-cli` if you want to set the git credential as well.\n",
199
+ "Token is valid (permission: fineGrained).\n",
200
+ "Your token has been saved to /root/.cache/huggingface/token\n",
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+ "Login successful\n"
202
+ ]
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+ }
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "source": [
209
+ "import spaces\n",
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+ "import gradio as gr\n",
211
+ "import torch\n",
212
+ "from PIL import Image\n",
213
+ "from diffusers import DiffusionPipeline\n",
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+ "import random\n",
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+ "import uuid\n",
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+ "from typing import Tuple\n",
217
+ "import numpy as np\n",
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+ "\n",
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+ "DESCRIPTIONz = \"\"\"## FLUX REALISM 🔥\"\"\"\n",
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+ "\n",
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+ "def save_image(img):\n",
222
+ " unique_name = str(uuid.uuid4()) + \".png\"\n",
223
+ " img.save(unique_name)\n",
224
+ " return unique_name\n",
225
+ "\n",
226
+ "def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:\n",
227
+ " if randomize_seed:\n",
228
+ " seed = random.randint(0, MAX_SEED)\n",
229
+ " return seed\n",
230
+ "\n",
231
+ "MAX_SEED = np.iinfo(np.int32).max\n",
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+ "\n",
233
+ "if not torch.cuda.is_available():\n",
234
+ " DESCRIPTIONz += \"\\n<p>⚠️Running on CPU, This may not work on CPU.</p>\"\n",
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+ "\n",
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+ "base_model = \"black-forest-labs/FLUX.1-dev\"\n",
237
+ "pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)\n",
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+ "\n",
239
+ "lora_repo = \"prithivMLmods/Canopus-LoRA-Flux-FaceRealism\"\n",
240
+ "trigger_word = \"Realism\" # Leave trigger_word blank if not used.\n",
241
+ "pipe.load_lora_weights(lora_repo)\n",
242
+ "\n",
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+ "pipe.to(\"cuda\")\n",
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+ "\n",
245
+ "style_list = [\n",
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+ " {\n",
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+ " \"name\": \"3840 x 2160\",\n",
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+ " \"prompt\": \"hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic\",\n",
249
+ " },\n",
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+ " {\n",
251
+ " \"name\": \"2560 x 1440\",\n",
252
+ " \"prompt\": \"hyper-realistic 4K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic\",\n",
253
+ " },\n",
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+ " {\n",
255
+ " \"name\": \"HD+\",\n",
256
+ " \"prompt\": \"hyper-realistic 2K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic\",\n",
257
+ " },\n",
258
+ " {\n",
259
+ " \"name\": \"Style Zero\",\n",
260
+ " \"prompt\": \"{prompt}\",\n",
261
+ " },\n",
262
+ "]\n",
263
+ "\n",
264
+ "styles = {k[\"name\"]: k[\"prompt\"] for k in style_list}\n",
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+ "\n",
266
+ "DEFAULT_STYLE_NAME = \"3840 x 2160\"\n",
267
+ "STYLE_NAMES = list(styles.keys())\n",
268
+ "\n",
269
+ "def apply_style(style_name: str, positive: str) -> str:\n",
270
+ " return styles.get(style_name, styles[DEFAULT_STYLE_NAME]).replace(\"{prompt}\", positive)\n",
271
+ "\n",
272
+ "@spaces.GPU(duration=60, enable_queue=True)\n",
273
+ "def generate(\n",
274
+ " prompt: str,\n",
275
+ " seed: int = 0,\n",
276
+ " width: int = 1024,\n",
277
+ " height: int = 1024,\n",
278
+ " guidance_scale: float = 3,\n",
279
+ " randomize_seed: bool = False,\n",
280
+ " style_name: str = DEFAULT_STYLE_NAME,\n",
281
+ " progress=gr.Progress(track_tqdm=True),\n",
282
+ "):\n",
283
+ " seed = int(randomize_seed_fn(seed, randomize_seed))\n",
284
+ "\n",
285
+ " positive_prompt = apply_style(style_name, prompt)\n",
286
+ "\n",
287
+ " if trigger_word:\n",
288
+ " positive_prompt = f\"{trigger_word} {positive_prompt}\"\n",
289
+ "\n",
290
+ " images = pipe(\n",
291
+ " prompt=positive_prompt,\n",
292
+ " width=width,\n",
293
+ " height=height,\n",
294
+ " guidance_scale=guidance_scale,\n",
295
+ " num_inference_steps=16,\n",
296
+ " num_images_per_prompt=1,\n",
297
+ " output_type=\"pil\",\n",
298
+ " ).images\n",
299
+ " image_paths = [save_image(img) for img in images]\n",
300
+ " print(image_paths)\n",
301
+ " return image_paths, seed\n",
302
+ "\n",
303
+ "\n",
304
+ "def load_predefined_images():\n",
305
+ " predefined_images = [\n",
306
+ " \"assets/11.png\",\n",
307
+ " \"assets/22.png\",\n",
308
+ " \"assets/33.png\",\n",
309
+ " \"assets/44.png\",\n",
310
+ " \"assets/55.webp\",\n",
311
+ " \"assets/66.png\",\n",
312
+ " \"assets/77.png\",\n",
313
+ " \"assets/88.png\",\n",
314
+ " \"assets/99.png\",\n",
315
+ " ]\n",
316
+ " return predefined_images\n",
317
+ "\n",
318
+ "\n",
319
+ "\n",
320
+ "examples = [\n",
321
+ " \"A portrait of an attractive woman in her late twenties with light brown hair and purple, wearing large a a yellow sweater. She is looking directly at the camera, standing outdoors near trees.. --ar 128:85 --v 6.0 --style raw\",\n",
322
+ " \"A photo of the model wearing a white bodysuit and beige trench coat, posing in front of a train station with hands on head, soft light, sunset, fashion photography, high resolution, 35mm lens, f/22, natural lighting, global illumination. --ar 85:128 --v 6.0 --style raw\",\n",
323
+ "]\n",
324
+ "\n",
325
+ "\n",
326
+ "css = '''\n",
327
+ ".gradio-container{max-width: 575px !important}\n",
328
+ "h1{text-align:center}\n",
329
+ "footer {\n",
330
+ " visibility: hidden\n",
331
+ "}\n",
332
+ "'''\n",
333
+ "\n",
334
+ "with gr.Blocks(css=css, theme=\"bethecloud/storj_theme\") as demo:\n",
335
+ " gr.Markdown(DESCRIPTIONz)\n",
336
+ " with gr.Row():\n",
337
+ " prompt = gr.Text(\n",
338
+ " label=\"Prompt\",\n",
339
+ " show_label=False,\n",
340
+ " max_lines=1,\n",
341
+ " placeholder=\"Enter your prompt\",\n",
342
+ " container=False,\n",
343
+ " )\n",
344
+ " run_button = gr.Button(\"Run\", scale=0)\n",
345
+ " result = gr.Gallery(label=\"Result\", columns=1, show_label=False)\n",
346
+ "\n",
347
+ " with gr.Accordion(\"Advanced options\", open=False, visible=True):\n",
348
+ " seed = gr.Slider(\n",
349
+ " label=\"Seed\",\n",
350
+ " minimum=0,\n",
351
+ " maximum=MAX_SEED,\n",
352
+ " step=1,\n",
353
+ " value=0,\n",
354
+ " visible=True\n",
355
+ " )\n",
356
+ " randomize_seed = gr.Checkbox(label=\"Randomize seed\", value=True)\n",
357
+ "\n",
358
+ " with gr.Row(visible=True):\n",
359
+ " width = gr.Slider(\n",
360
+ " label=\"Width\",\n",
361
+ " minimum=512,\n",
362
+ " maximum=2048,\n",
363
+ " step=64,\n",
364
+ " value=1024,\n",
365
+ " )\n",
366
+ " height = gr.Slider(\n",
367
+ " label=\"Height\",\n",
368
+ " minimum=512,\n",
369
+ " maximum=2048,\n",
370
+ " step=64,\n",
371
+ " value=1024,\n",
372
+ " )\n",
373
+ "\n",
374
+ " with gr.Row():\n",
375
+ " guidance_scale = gr.Slider(\n",
376
+ " label=\"Guidance Scale\",\n",
377
+ " minimum=0.1,\n",
378
+ " maximum=20.0,\n",
379
+ " step=0.1,\n",
380
+ " value=3.0,\n",
381
+ " )\n",
382
+ " num_inference_steps = gr.Slider(\n",
383
+ " label=\"Number of inference steps\",\n",
384
+ " minimum=1,\n",
385
+ " maximum=40,\n",
386
+ " step=1,\n",
387
+ " value=16,\n",
388
+ " )\n",
389
+ "\n",
390
+ " style_selection = gr.Radio(\n",
391
+ " show_label=True,\n",
392
+ " container=True,\n",
393
+ " interactive=True,\n",
394
+ " choices=STYLE_NAMES,\n",
395
+ " value=DEFAULT_STYLE_NAME,\n",
396
+ " label=\"Quality Style\",\n",
397
+ " )\n",
398
+ "\n",
399
+ "\n",
400
+ "\n",
401
+ " gr.Examples(\n",
402
+ " examples=examples,\n",
403
+ " inputs=prompt,\n",
404
+ " outputs=[result, seed],\n",
405
+ " fn=generate,\n",
406
+ " cache_examples=False,\n",
407
+ " )\n",
408
+ "\n",
409
+ " gr.on(\n",
410
+ " triggers=[\n",
411
+ " prompt.submit,\n",
412
+ " run_button.click,\n",
413
+ " ],\n",
414
+ " fn=generate,\n",
415
+ " inputs=[\n",
416
+ " prompt,\n",
417
+ " seed,\n",
418
+ " width,\n",
419
+ " height,\n",
420
+ " guidance_scale,\n",
421
+ " randomize_seed,\n",
422
+ " style_selection,\n",
423
+ " ],\n",
424
+ " outputs=[result, seed],\n",
425
+ " api_name=\"run\",\n",
426
+ " )\n",
427
+ "\n",
428
+ " gr.Markdown(\"### Generated Images\")\n",
429
+ " predefined_gallery = gr.Gallery(label=\"Generated Images\", columns=3, show_label=False, value=load_predefined_images())\n",
430
+ " gr.Markdown(\"**Disclaimer/Note:**\")\n",
431
+ "\n",
432
+ " gr.Markdown(\"🔥This space provides realistic image generation, which works better for human faces and portraits. Realistic trigger works properly, better for photorealistic trigger words, close-up shots, face diffusion, male, female characters.\")\n",
433
+ "\n",
434
+ " gr.Markdown(\"🔥users are accountable for the content they generate and are responsible for ensuring it meets appropriate ethical standards.\")\n",
435
+ "\n",
436
+ "if __name__ == \"__main__\":\n",
437
+ " demo.queue(max_size=40).launch()"
438
+ ],
439
+ "metadata": {
440
+ "id": "35LXnZWVaBZ_"
441
+ },
442
+ "execution_count": null,
443
+ "outputs": []
444
+ }
445
+ ]
446
+ }