Spaces:
Running
on
Zero
Running
on
Zero
upload app
#3
by
prithivMLmods
- opened
- app.py +315 -0
- requirements.txt +14 -0
app.py
ADDED
@@ -0,0 +1,315 @@
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1 |
+
import os
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2 |
+
import time
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3 |
+
import threading
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4 |
+
import gradio as gr
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5 |
+
import spaces
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6 |
+
import torch
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7 |
+
import numpy as np
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8 |
+
from PIL import Image
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9 |
+
import cv2
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10 |
+
from transformers import (
|
11 |
+
Qwen2_5_VLForConditionalGeneration,
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12 |
+
Qwen2VLForConditionalGeneration,
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13 |
+
Glm4vForConditionalGeneration,
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14 |
+
AutoProcessor,
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15 |
+
TextIteratorStreamer,
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16 |
+
)
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17 |
+
from qwen_vl_utils import process_vision_info
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18 |
+
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19 |
+
# Constants for text generation
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20 |
+
MAX_MAX_NEW_TOKENS = 4096
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21 |
+
DEFAULT_MAX_NEW_TOKENS = 3584
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22 |
+
MAX_INPUT_TOKEN_LENGTH = int(os.getenv("MAX_INPUT_TOKEN_LENGTH", "4096"))
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23 |
+
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24 |
+
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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25 |
+
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26 |
+
# Load Camel-Doc-OCR-062825
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27 |
+
MODEL_ID_M = "prithivMLmods/Camel-Doc-OCR-062825"
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28 |
+
processor_m = AutoProcessor.from_pretrained(MODEL_ID_M, trust_remote_code=True)
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29 |
+
model_m = Qwen2_5_VLForConditionalGeneration.from_pretrained(
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30 |
+
MODEL_ID_M,
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31 |
+
trust_remote_code=True,
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32 |
+
torch_dtype=torch.float16
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33 |
+
).to(device).eval()
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34 |
+
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35 |
+
# Load Qwen2.5-VL-3B-Instruct-abliterated
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36 |
+
MODEL_ID_X = "huihui-ai/Qwen2.5-VL-3B-Instruct-abliterated"
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37 |
+
processor_x = AutoProcessor.from_pretrained(MODEL_ID_X, trust_remote_code=True)
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38 |
+
model_x = Qwen2_5_VLForConditionalGeneration.from_pretrained(
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39 |
+
MODEL_ID_X,
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40 |
+
trust_remote_code=True,
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41 |
+
torch_dtype=torch.float16
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42 |
+
).to(device).eval()
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43 |
+
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44 |
+
# Load Megalodon-OCR-Sync-0713
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45 |
+
MODEL_ID_T = "prithivMLmods/Megalodon-OCR-Sync-0713"
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46 |
+
processor_t = AutoProcessor.from_pretrained(MODEL_ID_T, trust_remote_code=True)
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47 |
+
model_t = Qwen2_5_VLForConditionalGeneration.from_pretrained(
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48 |
+
MODEL_ID_T,
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49 |
+
trust_remote_code=True,
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50 |
+
torch_dtype=torch.float16
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51 |
+
).to(device).eval()
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52 |
+
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53 |
+
# Load GLM-4.1V-9B-Thinking
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54 |
+
MODEL_ID_S = "zai-org/GLM-4.1V-9B-Thinking"
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55 |
+
processor_s = AutoProcessor.from_pretrained(MODEL_ID_S, trust_remote_code=True)
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56 |
+
model_s = Glm4vForConditionalGeneration.from_pretrained(
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57 |
+
MODEL_ID_S,
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58 |
+
trust_remote_code=True,
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59 |
+
torch_dtype=torch.float16
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60 |
+
).to(device).eval()
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61 |
+
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62 |
+
# Load DeepEyes-7B
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63 |
+
MODEL_ID_Y = "ChenShawn/DeepEyes-7B"
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64 |
+
processor_y = AutoProcessor.from_pretrained(MODEL_ID_Y, trust_remote_code=True)
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65 |
+
model_y = Qwen2_5_VLForConditionalGeneration.from_pretrained(
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66 |
+
MODEL_ID_Y,
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67 |
+
trust_remote_code=True,
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68 |
+
torch_dtype=torch.float16
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69 |
+
).to(device).eval()
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70 |
+
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71 |
+
def downsample_video(video_path):
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72 |
+
"""
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73 |
+
Downsample a video to evenly spaced frames, returning each as a PIL image with its timestamp.
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74 |
+
"""
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75 |
+
vidcap = cv2.VideoCapture(video_path)
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76 |
+
total_frames = int(vidcap.get(cv2.CAP_PROP_FRAME_COUNT))
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77 |
+
fps = vidcap.get(cv2.CAP_PROP_FPS)
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78 |
+
frames = []
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79 |
+
frame_indices = np.linspace(0, total_frames - 1, 10, dtype=int)
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80 |
+
for i in frame_indices:
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81 |
+
vidcap.set(cv2.CAP_PROP_POS_FRAMES, i)
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82 |
+
success, image = vidcap.read()
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83 |
+
if success:
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84 |
+
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
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85 |
+
pil_image = Image.fromarray(image)
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86 |
+
timestamp = round(i / fps, 2)
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87 |
+
frames.append((pil_image, timestamp))
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88 |
+
vidcap.release()
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89 |
+
return frames
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90 |
+
|
91 |
+
@spaces.GPU
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92 |
+
def generate_image(model_name: str, text: str, image: Image.Image,
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93 |
+
max_new_tokens: int = 1024,
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94 |
+
temperature: float = 0.6,
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95 |
+
top_p: float = 0.9,
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96 |
+
top_k: int = 50,
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97 |
+
repetition_penalty: float = 1.2):
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98 |
+
"""
|
99 |
+
Generate responses using the selected model for image input.
|
100 |
+
"""
|
101 |
+
if model_name == "Camel-Doc-OCR-062825":
|
102 |
+
processor = processor_m
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103 |
+
model = model_m
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104 |
+
elif model_name == "Megalodon-OCR-Sync-0713":
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105 |
+
processor = processor_t
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106 |
+
model = model_t
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107 |
+
elif model_name == "GLM-4.1V-9B-Thinking":
|
108 |
+
processor = processor_s
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109 |
+
model = model_s
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110 |
+
elif model_name == "DeepEyes-7B-Thinking":
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111 |
+
processor = processor_y
|
112 |
+
model = model_y
|
113 |
+
elif model_name == "Qwen2.5-VL-3B-Instruct-abliterated":
|
114 |
+
processor = processor_x
|
115 |
+
model = model_x
|
116 |
+
else:
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117 |
+
yield "Invalid model selected.", "Invalid model selected."
|
118 |
+
return
|
119 |
+
|
120 |
+
if image is None:
|
121 |
+
yield "Please upload an image.", "Please upload an image."
|
122 |
+
return
|
123 |
+
|
124 |
+
messages = [{
|
125 |
+
"role": "user",
|
126 |
+
"content": [
|
127 |
+
{"type": "image", "image": image},
|
128 |
+
{"type": "text", "text": text},
|
129 |
+
]
|
130 |
+
}]
|
131 |
+
prompt_full = processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
|
132 |
+
inputs = processor(
|
133 |
+
text=[prompt_full],
|
134 |
+
images=[image],
|
135 |
+
return_tensors="pt",
|
136 |
+
padding=True,
|
137 |
+
truncation=False,
|
138 |
+
max_length=MAX_INPUT_TOKEN_LENGTH
|
139 |
+
).to(device)
|
140 |
+
streamer = TextIteratorStreamer(processor, skip_prompt=True, skip_special_tokens=True)
|
141 |
+
generation_kwargs = {**inputs, "streamer": streamer, "max_new_tokens": max_new_tokens}
|
142 |
+
thread = threading.Thread(target=model.generate, kwargs=generation_kwargs)
|
143 |
+
thread.start()
|
144 |
+
buffer = ""
|
145 |
+
for new_text in streamer:
|
146 |
+
buffer += new_text
|
147 |
+
time.sleep(0.01)
|
148 |
+
yield buffer, buffer
|
149 |
+
|
150 |
+
@spaces.GPU
|
151 |
+
def generate_video(model_name: str, text: str, video_path: str,
|
152 |
+
max_new_tokens: int = 1024,
|
153 |
+
temperature: float = 0.6,
|
154 |
+
top_p: float = 0.9,
|
155 |
+
top_k: int = 50,
|
156 |
+
repetition_penalty: float = 1.2):
|
157 |
+
"""
|
158 |
+
Generate responses using the selected model for video input.
|
159 |
+
"""
|
160 |
+
if model_name == "Camel-Doc-OCR-062825":
|
161 |
+
processor = processor_m
|
162 |
+
model = model_m
|
163 |
+
elif model_name == "Megalodon-OCR-Sync-0713":
|
164 |
+
processor = processor_t
|
165 |
+
model = model_t
|
166 |
+
elif model_name == "GLM-4.1V-9B-Thinking":
|
167 |
+
processor = processor_s
|
168 |
+
model = model_s
|
169 |
+
elif model_name == "DeepEyes-7B-Thinking":
|
170 |
+
processor = processor_y
|
171 |
+
model = model_y
|
172 |
+
elif model_name == "Qwen2.5-VL-3B-Instruct-abliterated":
|
173 |
+
processor = processor_x
|
174 |
+
model = model_x
|
175 |
+
else:
|
176 |
+
yield "Invalid model selected.", "Invalid model selected."
|
177 |
+
return
|
178 |
+
|
179 |
+
if video_path is None:
|
180 |
+
yield "Please upload a video.", "Please upload a video."
|
181 |
+
return
|
182 |
+
|
183 |
+
frames = downsample_video(video_path)
|
184 |
+
messages = [
|
185 |
+
{"role": "system", "content": [{"type": "text", "text": "You are a helpful assistant."}]},
|
186 |
+
{"role": "user", "content": [{"type": "text", "text": text}]}
|
187 |
+
]
|
188 |
+
for frame in frames:
|
189 |
+
image, timestamp = frame
|
190 |
+
messages[1]["content"].append({"type": "text", "text": f"Frame {timestamp}:"})
|
191 |
+
messages[1]["content"].append({"type": "image", "image": image})
|
192 |
+
inputs = processor.apply_chat_template(
|
193 |
+
messages,
|
194 |
+
tokenize=True,
|
195 |
+
add_generation_prompt=True,
|
196 |
+
return_dict=True,
|
197 |
+
return_tensors="pt",
|
198 |
+
truncation=False,
|
199 |
+
max_length=MAX_INPUT_TOKEN_LENGTH
|
200 |
+
).to(device)
|
201 |
+
streamer = TextIteratorStreamer(processor, skip_prompt=True, skip_special_tokens=True)
|
202 |
+
generation_kwargs = {
|
203 |
+
**inputs,
|
204 |
+
"streamer": streamer,
|
205 |
+
"max_new_tokens": max_new_tokens,
|
206 |
+
"do_sample": True,
|
207 |
+
"temperature": temperature,
|
208 |
+
"top_p": top_p,
|
209 |
+
"top_k": top_k,
|
210 |
+
"repetition_penalty": repetition_penalty,
|
211 |
+
}
|
212 |
+
thread = threading.Thread(target=model.generate, kwargs=generation_kwargs)
|
213 |
+
thread.start()
|
214 |
+
buffer = ""
|
215 |
+
for new_text in streamer:
|
216 |
+
buffer += new_text
|
217 |
+
buffer = buffer.replace("<|im_end|>", "")
|
218 |
+
time.sleep(0.01)
|
219 |
+
yield buffer, buffer
|
220 |
+
|
221 |
+
# Define examples for image and video inference
|
222 |
+
image_examples = [
|
223 |
+
["explain the movie shot in detail.", "images/5.jpg"],
|
224 |
+
["convert this page to doc [text] precisely for markdown.", "images/1.png"],
|
225 |
+
["convert this page to doc [table] precisely for markdown.", "images/2.png"],
|
226 |
+
["explain the movie shot in detail.", "images/3.png"],
|
227 |
+
["fill the correct numbers.", "images/4.png"]
|
228 |
+
]
|
229 |
+
|
230 |
+
video_examples = [
|
231 |
+
["explain the video in detail.", "videos/b.mp4"],
|
232 |
+
["explain the ad video in detail.", "videos/a.mp4"]
|
233 |
+
]
|
234 |
+
|
235 |
+
# Updated CSS with model choice highlighting
|
236 |
+
css = """
|
237 |
+
.submit-btn {
|
238 |
+
background-color: #2980b9 !important;
|
239 |
+
color: white !important;
|
240 |
+
}
|
241 |
+
.submit-btn:hover {
|
242 |
+
background-color: #3498db !important;
|
243 |
+
}
|
244 |
+
.canvas-output {
|
245 |
+
border: 2px solid #4682B4;
|
246 |
+
border-radius: 10px;
|
247 |
+
padding: 20px;
|
248 |
+
}
|
249 |
+
"""
|
250 |
+
|
251 |
+
# Create the Gradio Interface
|
252 |
+
with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
|
253 |
+
gr.Markdown("# **[Multimodal VLM OCR](https://huggingface.co/collections/prithivMLmods/multimodal-implementations-67c9982ea04b39f0608badb0)**")
|
254 |
+
with gr.Row():
|
255 |
+
with gr.Column():
|
256 |
+
with gr.Tabs():
|
257 |
+
with gr.TabItem("Image Inference"):
|
258 |
+
image_query = gr.Textbox(label="Query Input", placeholder="Enter your query here...")
|
259 |
+
image_upload = gr.Image(type="pil", label="Image")
|
260 |
+
image_submit = gr.Button("Submit", elem_classes="submit-btn")
|
261 |
+
gr.Examples(
|
262 |
+
examples=image_examples,
|
263 |
+
inputs=[image_query, image_upload]
|
264 |
+
)
|
265 |
+
with gr.TabItem("Video Inference"):
|
266 |
+
video_query = gr.Textbox(label="Query Input", placeholder="Enter your query here...")
|
267 |
+
video_upload = gr.Video(label="Video")
|
268 |
+
video_submit = gr.Button("Submit", elem_classes="submit-btn")
|
269 |
+
gr.Examples(
|
270 |
+
examples=video_examples,
|
271 |
+
inputs=[video_query, video_upload]
|
272 |
+
)
|
273 |
+
|
274 |
+
with gr.Accordion("Advanced options", open=False):
|
275 |
+
max_new_tokens = gr.Slider(label="Max new tokens", minimum=1, maximum=MAX_MAX_NEW_TOKENS, step=1, value=DEFAULT_MAX_NEW_TOKENS)
|
276 |
+
temperature = gr.Slider(label="Temperature", minimum=0.1, maximum=4.0, step=0.1, value=0.6)
|
277 |
+
top_p = gr.Slider(label="Top-p (nucleus sampling)", minimum=0.05, maximum=1.0, step=0.05, value=0.9)
|
278 |
+
top_k = gr.Slider(label="Top-k", minimum=1, maximum=1000, step=1, value=50)
|
279 |
+
repetition_penalty = gr.Slider(label="Repetition penalty", minimum=1.0, maximum=2.0, step=0.05, value=1.2)
|
280 |
+
|
281 |
+
with gr.Column():
|
282 |
+
with gr.Column(elem_classes="canvas-output"):
|
283 |
+
gr.Markdown("## Output")
|
284 |
+
output = gr.Textbox(label="Raw Output Stream", interactive=False, lines=2)
|
285 |
+
with gr.Accordion("(Result.md)", open=False):
|
286 |
+
markdown_output = gr.Markdown(label="(Result.md)")
|
287 |
+
|
288 |
+
model_choice = gr.Radio(
|
289 |
+
choices=["Camel-Doc-OCR-062825", "GLM-4.1V-9B-Thinking", "Megalodon-OCR-Sync-0713", "DeepEyes-7B-Thinking", "Qwen2.5-VL-3B-Instruct-abliterated"],
|
290 |
+
label="Select Model",
|
291 |
+
value="Camel-Doc-OCR-062825"
|
292 |
+
)
|
293 |
+
gr.Markdown("**Model Info 💻** | [Report Bug](https://huggingface.co/spaces/prithivMLmods/Multimodal-OCR-Comparator/discussions)")
|
294 |
+
gr.Markdown("> Camel-Doc-OCR-062825 and Megalodon-OCR-Sync-0713 are both fine-tuned versions of the Qwen2.5-VL series focused on document retrieval, content extraction, analysis recognition, and excelling in OCR and visual document analysis tasks for structured and unstructured content—Camel-Doc-OCR-062825 leveraging the Qwen2.5-VL-7B-Instruct as its base, while Megalodon-OCR-Sync-0713 uses Qwen2.5-VL-3B-Instruct and is especially trained on diverse captioning datasets.")
|
295 |
+
gr.Markdown("> GLM-4.1V-9B-Thinking is a vision-language model (VLM) based on the GLM-4-9B-0414 foundation, with a strong emphasis on advanced reasoning capabilities, chain-of-thought inference, and robust bilingual (Chinese/English) performance on complex multimodal benchmarks.")
|
296 |
+
gr.Markdown("> DeepEyes-7B stands out for its agentic reinforcement learning approach, focusing on thinking with images for better visual reasoning, math problem-solving, and mitigating hallucination using Qwen2.5-VL-7B-Instruct as its foundation. Finally, Qwen2.5-VL-3B-Instruct-abliterated is part of the Qwen2.5-VL family, known for its versatile vision-language understanding and generation, serving as the foundational architecture for several of these fine-tuned vision-language and OCR models.")
|
297 |
+
|
298 |
+
# Define the submit button actions
|
299 |
+
image_submit.click(fn=generate_image,
|
300 |
+
inputs=[
|
301 |
+
model_choice, image_query, image_upload,
|
302 |
+
max_new_tokens, temperature, top_p, top_k,
|
303 |
+
repetition_penalty
|
304 |
+
],
|
305 |
+
outputs=[output, markdown_output])
|
306 |
+
video_submit.click(fn=generate_video,
|
307 |
+
inputs=[
|
308 |
+
model_choice, video_query, video_upload,
|
309 |
+
max_new_tokens, temperature, top_p, top_k,
|
310 |
+
repetition_penalty
|
311 |
+
],
|
312 |
+
outputs=[output, markdown_output])
|
313 |
+
|
314 |
+
if __name__ == "__main__":
|
315 |
+
demo.queue(max_size=30).launch(share=True, mcp_server=True, ssr_mode=False, show_error=True)
|
requirements.txt
ADDED
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
gradio
|
2 |
+
numpy
|
3 |
+
transformers
|
4 |
+
transformers-stream-generator
|
5 |
+
qwen-vl-utils
|
6 |
+
torchvision
|
7 |
+
torch
|
8 |
+
requests
|
9 |
+
huggingface-hub
|
10 |
+
spaces
|
11 |
+
accelerate
|
12 |
+
pillow
|
13 |
+
opencv-python
|
14 |
+
av
|