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model.py
CHANGED
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@@ -28,6 +28,11 @@ from cldm.model import create_model, load_state_dict
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from ldm.models.diffusion.ddim import DDIMSampler
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from share import *
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ORIGINAL_MODEL_NAMES = {
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'canny': 'control_sd15_canny.pth',
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'hough': 'control_sd15_mlsd.pth',
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@@ -632,9 +637,9 @@ class Model:
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results = [x_samples[i] for i in range(num_samples)]
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print(f"type of results ^^ - {type(results)}")
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print(f"
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-
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filename = results[0] #['name']
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#def encode(img_array):
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print(f"type of input_image ^^ - {type(input_image)}")
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@@ -655,7 +660,8 @@ class Model:
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htmltag = '<img src= "data:image/jpeg;base64,' + encoded_string + '" alt="Original Image"/></div> <img src= "https://ysharma-controlnet-image-comparison.hf.space/file=' + filename + '" alt="Control Net Image"/>'
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#https://ysharma-controlnet-image-comparison.hf.space/file=/tmp/tmpg4qx22xy.png - sample
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print(f"htmltag is ^^ - {htmltag}")
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<!DOCTYPE html>
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<html lang="en">
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<head>
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@@ -704,12 +710,13 @@ class Model:
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<body>
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<div style="margin: 3rem;
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font-family: Roboto, sans-serif">
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<
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</div> <div> <div class="image-slider"> <div>
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#return desc
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return [detected_map] + results, desc
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@torch.inference_mode()
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def process_depth(self, input_image, prompt, a_prompt, n_prompt,
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from ldm.models.diffusion.ddim import DDIMSampler
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from share import *
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from PIL import Image
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import gradio as gr
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import numpy as np
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import base64
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ORIGINAL_MODEL_NAMES = {
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'canny': 'control_sd15_canny.pth',
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'hough': 'control_sd15_mlsd.pth',
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results = [x_samples[i] for i in range(num_samples)]
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tmp = """print(f"type of results ^^ - {type(results)}")
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print(f"length of results list ^^ - {len(results)}")
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print(f"value of results[0] ^^ - {results[0]}")
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filename = results[0] #['name']
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#def encode(img_array):
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print(f"type of input_image ^^ - {type(input_image)}")
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htmltag = '<img src= "data:image/jpeg;base64,' + encoded_string + '" alt="Original Image"/></div> <img src= "https://ysharma-controlnet-image-comparison.hf.space/file=' + filename + '" alt="Control Net Image"/>'
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#https://ysharma-controlnet-image-comparison.hf.space/file=/tmp/tmpg4qx22xy.png - sample
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print(f"htmltag is ^^ - {htmltag}")
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desc =
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<body>
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<div style="margin: 3rem;
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font-family: Roboto, sans-serif">
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<h4 style="color: green"> Observe the Ingenuity of ControlNet by comparing Input and Output images</h4>
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</div> <div> <div class="image-slider"> <div> + htmltag + "</div> </div> </body> </html> "
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#return desc
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"""
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return results[0] #[detected_map] + results, desc
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@torch.inference_mode()
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def process_depth(self, input_image, prompt, a_prompt, n_prompt,
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