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app.py

@@ -20,7 +20,7 @@ MAX_PIXELS = 1344 * 28 * 28
 
 # Load the model
 model = Qwen2VLForConditionalGeneration.from_pretrained(
-    "showlab/ShowUI-2B",
+    "./showui-2b",
     torch_dtype=torch.bfloat16,
     device_map="auto",
 )
@@ -246,4 +246,4 @@ if __name__ == "__main__":
         server_name="0.0.0.0",
         server_port=7860,
         share=True
-    )
+    )

showui-2b/.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
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+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
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+*.model filter=lfs diff=lfs merge=lfs -text
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+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
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showui-2b/README.md

@@ -0,0 +1,188 @@
+---
+tags:
+- GUI agents
+- vision-language-action model
+- computer use
+---
+[Github](https://github.com/showlab/ShowUI/tree/main) | [Quick Start](https://huggingface.co/showlab/ShowUI-2B)
+<img src="examples/showui.png" alt="ShowUI" width="640">
+
+ShowUI is a lightweight (2B) vision-language-action model designed for GUI agents.
+[![demo](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Models-blue)](https://huggingface.co/showlab/ShowUI-2B)&nbsp;
+## ⭐ Quick Start
+
+1. Load model
+```python
+import ast
+import torch
+from PIL import Image, ImageDraw
+from qwen_vl_utils import process_vision_info
+from transformers import Qwen2VLForConditionalGeneration, AutoTokenizer, AutoProcessor
+
+def draw_point(image_input, point=None, radius=5):
+    if isinstance(image_input, str):
+        image = Image.open(BytesIO(requests.get(image_input).content)) if image_input.startswith('http') else Image.open(image_input)
+    else:
+        image = image_input
+
+    if point:
+        x, y = point[0] * image.width, point[1] * image.height
+        ImageDraw.Draw(image).ellipse((x - radius, y - radius, x + radius, y + radius), fill='red')
+    display(image)
+    return
+
+model = Qwen2VLForConditionalGeneration.from_pretrained(
+    "showlab/ShowUI-2B",
+    torch_dtype=torch.bfloat16,
+    device_map="auto"
+)
+
+min_pixels = 256*28*28
+max_pixels = 1344*28*28
+
+processor = AutoProcessor.from_pretrained("Qwen/Qwen2-VL-2B-Instruct", min_pixels=min_pixels, max_pixels=max_pixels)
+```
+
+2. **UI Grounding**
+```python
+img_url = 'examples/web_dbd7514b-9ca3-40cd-b09a-990f7b955da1.png'
+query = "Nahant"
+
+
+_SYSTEM = "Based on the screenshot of the page, I give a text description and you give its corresponding location. The coordinate represents a clickable location [x, y] for an element, which is a relative coordinate on the screenshot, scaled from 0 to 1."
+messages = [
+    {
+        "role": "user",
+        "content": [
+            {"type": "text", "text": _SYSTEM},
+            {"type": "image", "image": img_url, "min_pixels": min_pixels, "max_pixels": max_pixels},
+            {"type": "text", "text": query}
+        ],
+    }
+]
+
+text = processor.apply_chat_template(
+    messages, tokenize=False, add_generation_prompt=True,
+)
+image_inputs, video_inputs = process_vision_info(messages)
+inputs = processor(
+    text=[text],
+    images=image_inputs,
+    videos=video_inputs,
+    padding=True,
+    return_tensors="pt",
+)
+inputs = inputs.to("cuda")
+
+generated_ids = model.generate(**inputs, max_new_tokens=128)
+generated_ids_trimmed = [
+    out_ids[len(in_ids) :] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)
+]
+output_text = processor.batch_decode(
+    generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
+)[0]
+
+click_xy = ast.literal_eval(output_text)
+# [0.73, 0.21]
+
+draw_point(img_url, click_xy, 10)
+```
+
+This will visualize the grounding results like (where the red points are [x,y])
+
+![download](https://github.com/user-attachments/assets/8fe2783d-05b6-44e6-a26c-8718d02b56cb)
+
+3. **UI Navigation**
+- Set up system prompt.
+```python
+_NAV_SYSTEM = """You are an assistant trained to navigate the {_APP} screen. 
+Given a task instruction, a screen observation, and an action history sequence, 
+output the next action and wait for the next observation. 
+Here is the action space:
+{_ACTION_SPACE}
+"""
+
+_NAV_FORMAT = """
+Format the action as a dictionary with the following keys:
+{'action': 'ACTION_TYPE', 'value': 'element', 'position': [x,y]}
+
+If value or position is not applicable, set it as `None`.
+Position might be [[x1,y1], [x2,y2]] if the action requires a start and end position.
+Position represents the relative coordinates on the screenshot and should be scaled to a range of 0-1.
+"""
+
+action_map = {
+'web': """
+1. `CLICK`: Click on an element, value is not applicable and the position [x,y] is required. 
+2. `INPUT`: Type a string into an element, value is a string to type and the position [x,y] is required. 
+3. `SELECT`: Select a value for an element, value is not applicable and the position [x,y] is required. 
+4. `HOVER`: Hover on an element, value is not applicable and the position [x,y] is required.
+5. `ANSWER`: Answer the question, value is the answer and the position is not applicable.
+6. `ENTER`: Enter operation, value and position are not applicable.
+7. `SCROLL`: Scroll the screen, value is the direction to scroll and the position is not applicable.
+8. `SELECT_TEXT`: Select some text content, value is not applicable and position [[x1,y1], [x2,y2]] is the start and end position of the select operation.
+9. `COPY`: Copy the text, value is the text to copy and the position is not applicable.
+""",
+
+'phone': """
+1. `INPUT`: Type a string into an element, value is not applicable and the position [x,y] is required. 
+2. `SWIPE`: Swipe the screen, value is not applicable and the position [[x1,y1], [x2,y2]] is the start and end position of the swipe operation.
+3. `TAP`: Tap on an element, value is not applicable and the position [x,y] is required.
+4. `ANSWER`: Answer the question, value is the status (e.g., 'task complete') and the position is not applicable.
+5. `ENTER`: Enter operation, value and position are not applicable.
+"""
+}
+
+_NAV_USER = """{system}
+Task: {task}
+Observation: <|image_1|>
+Action History: {action_history}
+What is the next action?
+"""
+```
+
+```python
+img_url = 'examples/chrome.png'
+split='web'
+system_prompt = _NAV_SYSTEM.format(_APP=split, _ACTION_SPACE=action_map[split])
+query = "Search the weather for the New York city."
+
+messages = [
+    {
+        "role": "user",
+        "content": [
+            {"type": "text", "text": system_prompt},
+            {"type": "image", "image": img_url, "min_pixels": min_pixels, "max_pixels": max_pixels},
+            {"type": "text", "text": query}
+        ],
+    }
+]
+
+text = processor.apply_chat_template(
+    messages, tokenize=False, add_generation_prompt=True,
+)
+image_inputs, video_inputs = process_vision_info(messages)
+inputs = processor(
+    text=[text],
+    images=image_inputs,
+    videos=video_inputs,
+    padding=True,
+    return_tensors="pt",
+)
+inputs = inputs.to("cuda")
+
+generated_ids = model.generate(**inputs, max_new_tokens=128)
+generated_ids_trimmed = [
+    out_ids[len(in_ids) :] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)
+]
+output_text = processor.batch_decode(
+    generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False
+)[0]
+
+print(output_text)
+# {'action': 'CLICK', 'value': None, 'position': [0.49, 0.42]},
+# {'action': 'INPUT', 'value': 'weather for New York city', 'position': [0.49, 0.42]},
+# {'action': 'ENTER', 'value': None, 'position': None}
+```
+
+![download](https://github.com/user-attachments/assets/624097ea-06f2-4c8f-83f6-b6b9ee439c0c)

showui-2b/added_tokens.json

@@ -0,0 +1,16 @@
+{
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644,
+  "<|image_pad|>": 151655,
+  "<|object_ref_end|>": 151647,
+  "<|object_ref_start|>": 151646,
+  "<|quad_end|>": 151651,
+  "<|quad_start|>": 151650,
+  "<|video_pad|>": 151656,
+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
+  "<|vision_start|>": 151652
+}

showui-2b/config.json

@@ -0,0 +1,48 @@
+{
+  "_name_or_path": "Qwen/Qwen2-VL-2B-Instruct",
+  "architectures": [
+    "Qwen2VLForConditionalGeneration"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151645,
+  "hidden_act": "silu",
+  "hidden_size": 1536,
+  "image_token_id": 151655,
+  "initializer_range": 0.02,
+  "intermediate_size": 8960,
+  "max_position_embeddings": 32768,
+  "max_window_layers": 28,
+  "model_type": "qwen2_vl",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 28,
+  "num_key_value_heads": 2,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": {
+    "mrope_section": [
+      16,
+      24,
+      24
+    ],
+    "type": "mrope"
+  },
+  "rope_theta": 1000000.0,
+  "sliding_window": 32768,
+  "tie_word_embeddings": true,
+  "tokenizer_model_max_length": 4096,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.45.0.dev0",
+  "use_cache": false,
+  "use_sliding_window": false,
+  "video_token_id": 151656,
+  "vision_config": {
+    "hidden_size": 1536,
+    "in_chans": 3,
+    "model_type": "qwen2_vl",
+    "spatial_patch_size": 14
+  },
+  "vision_end_token_id": 151653,
+  "vision_start_token_id": 151652,
+  "vision_token_id": 151654,
+  "vocab_size": 151936
+}

showui-2b/generation_config.json

@@ -0,0 +1,14 @@
+{
+  "_attn_implementation": "eager",
+  "bos_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "pad_token_id": 151643,
+  "temperature": 0.01,
+  "top_k": 1,
+  "top_p": 0.001,
+  "transformers_version": "4.45.0.dev0"
+}

showui-2b/preprocessor_config.json

@@ -0,0 +1,29 @@
+{
+  "do_convert_rgb": true,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.48145466,
+    0.4578275,
+    0.40821073
+  ],
+  "image_processor_type": "Qwen2VLImageProcessor",
+  "image_std": [
+    0.26862954,
+    0.26130258,
+    0.27577711
+  ],
+  "max_pixels": 12845056,
+  "merge_size": 2,
+  "min_pixels": 3136,
+  "patch_size": 14,
+  "processor_class": "Qwen2VLProcessor",
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "max_pixels": 12845056,
+    "min_pixels": 3136
+  },
+  "temporal_patch_size": 2
+}

showui-2b/pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:68080df785764e98976eb9cc93a07c6c69cf8a6933738496e02aef55b53d2aa3
+size 4418202778

showui-2b/special_tokens_map.json

@@ -0,0 +1,24 @@
+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

showui-2b/tokenizer_config.json

@@ -0,0 +1,144 @@
+{
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|object_ref_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151649": {
+      "content": "<|box_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n{% endif %}<|im_start|>{{ message['role'] }}\n{% if message['content'] is string %}{{ message['content'] }}<|im_end|>\n{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>\n{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant\n{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "model_max_length": 4096,
+  "pad_token": null,
+  "padding_side": "right",
+  "processor_class": "Qwen2VLProcessor",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}