update desc and safety checker
Browse files
app.py
CHANGED
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@@ -10,14 +10,14 @@ from diffusers import StableDiffusionInstructPix2PixPipeline, EulerAncestralDisc
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#Loading from Diffusers Library
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model_id = "timbrooks/instruct-pix2pix"
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pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained(model_id, torch_dtype=torch.float16, revision="fp16"
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pipe.to("cuda")
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pipe.enable_attention_slicing()
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counter = 0
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help_text = """ Note:
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Some notes from the official [instruct-pix2pix](https://huggingface.co/spaces/timbrooks/instruct-pix2pix) Space by the authors
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and from the official [Diffusers docs](https://huggingface.co/docs/diffusers/main/en/api/pipelines/stable_diffusion/pix2pix) -
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@@ -42,53 +42,38 @@ be to the input. This pipeline requires a value of at least `1`. It's possible y
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def chat(image_in, in_steps, in_guidance_scale, in_img_guidance_scale, image_hid, img_name, counter_out, prompt, history, progress=gr.Progress(track_tqdm=True)):
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progress(0, desc="Starting...")
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#if message == "revert": --to add revert functionality later
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print(f"counter:{counter_out}, prompt:{prompt}, img_name:{img_name}")
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if counter_out > 0:
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# Open the image
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#image_in = Image.open(img_name) #("edited_image.png") #(img_nm)
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edited_image = pipe(prompt, image=image_hid, num_inference_steps=int(in_steps), guidance_scale=float(in_guidance_scale), image_guidance_scale=float(in_img_guidance_scale)).images[0]
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if os.path.exists(img_name):
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print("***Image exists and will be deleted***")
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os.remove(img_name)
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temp_img_name = img_name[:-4]+str(int(time.time()))+'.png'
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print(f"temp_img_name is :{temp_img_name}")
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# Create a file-like object
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with open(temp_img_name, "wb") as fp:
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# Save the image to the file-like object
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edited_image.save(fp)
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#Get the name of the saved image
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saved_image_name = fp.name
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print(f"SAVED IMAGE NAME : {saved_image_name}, TMP IMAGE NAME : {temp_img_name}")
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#edited_image.save(temp_img_name) #, overwrite=True)
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counter_out += 1
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else:
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print("FIRST PASS")
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seed = random.randint(0, 1000000)
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img_name = f"./edited_image_{seed}.png"
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edited_image = pipe(prompt, image=image_in, num_inference_steps=int(in_steps), guidance_scale=float(in_guidance_scale), image_guidance_scale=float(in_img_guidance_scale)).images[0]
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if os.path.exists(img_name):
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print("***First PASS:Image exists and will be deleted***")
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os.remove(img_name)
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with open(img_name, "wb") as fp:
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# Save the image to the file-like object
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edited_image.save(fp)
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#Get the name of the saved image
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saved_image_name2 = fp.name
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print(f"SAVED IMAGE NAME : {saved_image_name2}, IMAGE NAME : {img_name}")
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#edited_image.save(img_name) #, overwrite=True) #("/tmp/edited_image.png") #(img_nm)
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#counter_out += 1
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history = history or []
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#Resizing (or not) the image for better display and adding supportive sample text
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add_text_list = ["There you go", "Enjoy your image!", "Nice work! Wonder what you gonna do next!", "Way to go!", "Does this work for you?", "Something like this?"]
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if counter_out > 0:
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-
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print(f"You are in {counter_out} pass")
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response = random.choice(add_text_list) + '<img src="/file=' + saved_image_name + '">' #temp_img_name
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history.append((prompt, response))
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return history, history, edited_image, temp_img_name, counter_out
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else:
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#response = edited_image
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print(f"You are in {counter_out} pass or FIRST Pass")
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response = random.choice(add_text_list) + '<img src="/file=' + saved_image_name2 + '">' #IMG_NAME
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history.append((prompt, response))
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counter_out += 1
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@@ -100,6 +85,10 @@ with gr.Blocks() as demo:
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<p>For faster inference without waiting in the queue, you may duplicate the space and upgrade to GPU in settings.<br/>
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<a href="https://huggingface.co/spaces/ysharma/InstructPix2Pix_Chatbot?duplicate=true">
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<img style="margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>
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<p/>""")
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with gr.Row():
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with gr.Column():
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#Loading from Diffusers Library
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model_id = "timbrooks/instruct-pix2pix"
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pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained(model_id, torch_dtype=torch.float16, revision="fp16") #, safety_checker=None)
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pipe.to("cuda")
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pipe.enable_attention_slicing()
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counter = 0
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help_text = """ Note: Functionality to revert your changes to previous/original image can be released in future versions. For now only forward editing is available.
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Some notes from the official [instruct-pix2pix](https://huggingface.co/spaces/timbrooks/instruct-pix2pix) Space by the authors
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and from the official [Diffusers docs](https://huggingface.co/docs/diffusers/main/en/api/pipelines/stable_diffusion/pix2pix) -
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def chat(image_in, in_steps, in_guidance_scale, in_img_guidance_scale, image_hid, img_name, counter_out, prompt, history, progress=gr.Progress(track_tqdm=True)):
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progress(0, desc="Starting...")
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#if message == "revert": --to add revert functionality later
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if counter_out > 0:
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edited_image = pipe(prompt, image=image_hid, num_inference_steps=int(in_steps), guidance_scale=float(in_guidance_scale), image_guidance_scale=float(in_img_guidance_scale)).images[0]
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if os.path.exists(img_name):
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os.remove(img_name)
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temp_img_name = img_name[:-4]+str(int(time.time()))+'.png'
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# Create a file-like object
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with open(temp_img_name, "wb") as fp:
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# Save the image to the file-like object
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edited_image.save(fp)
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#Get the name of the saved image
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saved_image_name = fp.name
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#edited_image.save(temp_img_name) #, overwrite=True)
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counter_out += 1
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else:
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seed = random.randint(0, 1000000)
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img_name = f"./edited_image_{seed}.png"
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edited_image = pipe(prompt, image=image_in, num_inference_steps=int(in_steps), guidance_scale=float(in_guidance_scale), image_guidance_scale=float(in_img_guidance_scale)).images[0]
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if os.path.exists(img_name):
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os.remove(img_name)
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with open(img_name, "wb") as fp:
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# Save the image to the file-like object
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edited_image.save(fp)
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#Get the name of the saved image
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saved_image_name2 = fp.name
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history = history or []
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#Resizing (or not) the image for better display and adding supportive sample text
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add_text_list = ["There you go", "Enjoy your image!", "Nice work! Wonder what you gonna do next!", "Way to go!", "Does this work for you?", "Something like this?"]
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if counter_out > 0:
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response = random.choice(add_text_list) + '<img src="/file=' + saved_image_name + '">'
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history.append((prompt, response))
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return history, history, edited_image, temp_img_name, counter_out
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else:
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response = random.choice(add_text_list) + '<img src="/file=' + saved_image_name2 + '">' #IMG_NAME
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history.append((prompt, response))
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counter_out += 1
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<p>For faster inference without waiting in the queue, you may duplicate the space and upgrade to GPU in settings.<br/>
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<a href="https://huggingface.co/spaces/ysharma/InstructPix2Pix_Chatbot?duplicate=true">
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<img style="margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>
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<b>Note: Please be advised that a safety checker has been implemented in this public space.
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Any attempts to generate inappropriate or NSFW images will result in the display of a black screen
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as a precautionary measure for the protection of all users. We appreciate your cooperation in
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maintaining a safe and appropriate environment for all members of our community.</b>
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<p/>""")
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with gr.Row():
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with gr.Column():
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