mstatt · August 31, 2024 06:21 · Aug 31, 2024
diff --git a/gistfile1.txt b/gistfile1.txt
@@ -0,0 +1,46 @@
+import os
+import cv2
+import torch
+from PIL import Image 
+from transformers import AutoProcessor ,AutoImageProcessor
+from transformers import AutoModelForCausalLM 
+
+
+## -------------------------------------------------------------------------------------------------------------------
+
+def run_phi3_model(image_path,prompt):
+
+    model_id = "microsoft/Phi-3-vision-128k-instruct" 
+
+    model = AutoModelForCausalLM.from_pretrained(model_id, device_map="cuda", trust_remote_code=True, torch_dtype="auto",attn_implementation="flash_attention_2")
+    processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True) 
+
+    messages = [ 
+        {"role": "user", "content": "<|image_1|>\n"+prompt}, 
+    ] 
+    # I will be using local images
+    image = Image.open(image_path) 
+    prompt = processor.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+    inputs = processor(prompt, [image], return_tensors="pt").to("cuda:0") 
+    generation_args = { 
+        "max_new_tokens": 1024, 
+        "temperature": 0.0, 
+        "do_sample": False, 
+    } 
+    generate_ids = model.generate(**inputs, eos_token_id=processor.tokenizer.eos_token_id, **generation_args) 
+    # remove input tokens 
+    generate_ids = generate_ids[:, inputs['input_ids'].shape[1]:]
+    response = processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0] 
+    del model
+    del processor
+    return response 
+
+
+## -------------------------------------------------------------------------------------------------------------------
+
+
+
+image_path = "1.png"
+prompt = "Identify the 4 most dominant colors in this image and return the hex values of these 4 dominant colors. Respond ONLY with a list of these hex values."
+results = run_phi3_model(image_path,prompt)
+print(results)
No results found