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- {
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- "name": "python"
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- "accelerator": "GPU"
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- "cells": [
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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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- "id": "L1CPm6HAZuTg",
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- "outputId": "3a85cb03-b18f-4e5b-8c5f-2f577bc46598"
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- "outputs": [
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- " Found existing installation: tomlkit 0.13.2\n",
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- " Uninstalling tomlkit-0.13.2:\n",
166
- " Successfully uninstalled tomlkit-0.13.2\n",
167
- "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"
168
- ]
169
- }
170
- ],
171
- "source": [
172
- "!pip install torch diffusers spaces transformers peft sentencepiece gradio"
173
- ]
174
- },
175
- {
176
- "cell_type": "code",
177
- "source": [
178
- "# Authenticate with Hugging Face\n",
179
- "from huggingface_hub import login\n",
180
- "\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",
196
- "name": "stdout",
197
- "text": [
198
- "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",
201
- "Login successful\n"
202
- ]
203
- }
204
- ]
205
- },
206
- {
207
- "cell_type": "code",
208
- "source": [
209
- "import spaces\n",
210
- "import gradio as gr\n",
211
- "import torch\n",
212
- "from PIL import Image\n",
213
- "from diffusers import DiffusionPipeline\n",
214
- "import random\n",
215
- "import uuid\n",
216
- "from typing import Tuple\n",
217
- "import numpy as np\n",
218
- "\n",
219
- "DESCRIPTIONz = \"\"\"## FLUX REALISM 🔥\"\"\"\n",
220
- "\n",
221
- "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",
232
- "\n",
233
- "if not torch.cuda.is_available():\n",
234
- " DESCRIPTIONz += \"\\n<p>⚠️Running on CPU, This may not work on CPU.</p>\"\n",
235
- "\n",
236
- "base_model = \"black-forest-labs/FLUX.1-dev\"\n",
237
- "pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)\n",
238
- "\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",
243
- "pipe.to(\"cuda\")\n",
244
- "\n",
245
- "style_list = [\n",
246
- " {\n",
247
- " \"name\": \"3840 x 2160\",\n",
248
- " \"prompt\": \"hyper-realistic 8K image of {prompt}. ultra-detailed, lifelike, high-resolution, sharp, vibrant colors, photorealistic\",\n",
249
- " },\n",
250
- " {\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",
254
- " {\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",
265
- "\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
- }