Adding more info on the README

README.md

@@ -15,6 +15,14 @@ pip install -r requirements.txt
 pip install -e <PATH TO LATEST TRANSFOMERS VERSION>
 ```
 
+## Running the demo
+
+Make sure to be connected using the wifi hotspot of the robomaster which is the most stable one.
+
+The default password for the hotpsot is: 12341234
+
+You might need to have a second wifi card if you want to be able to run the demo with internet on.
+
 ```bash
 export HF_TOKEN=<TOKEN>
 conda activate idefics2
@@ -23,3 +31,18 @@ conda activate idefics2
 dora up
 dora start graphs/dataflow_robot_vlm.yml --attach --hot-reload
 ```
+
+Current way to interact is by typing a question to the VLM
+
+## Running the demo without robot
+
+```bash
+export HF_TOKEN=<TOKEN>
+conda activate idefics2
+# This requires dora==0.3.3, update with:
+# cargo install dora-cli
+dora up
+dora start graphs/dataflow_vlm_basic.yml --attach --hot-reload
+```
+
+Current way to interact is by typing a question to the VLM

graphs/dataflow_vlm_basic.yml

@@ -5,17 +5,18 @@ nodes:
       python: ../operators/plot.py
       inputs:
         image: webcam/image
-        # keyboard_buffer: keyboard/buffer
-        # user_message: keyboard/submitted
+        keyboard_buffer: keyboard/buffer
+        user_message: keyboard/submitted
         assistant_message: vlm/assistant_message
 
   - id: vlm
     operator:
-      python: ../operators/chatgpt_op.py
+      python: ../operators/idefics2_op.py
       inputs: 
         image:
           source: webcam/image
           queue_size: 1
+        instruction: keyboard/submitted
       outputs:
         - assistant_message
   
@@ -23,6 +24,13 @@ nodes:
     operator:
       python: ../operators/webcam.py
       inputs:
-        tick: dora/timer/millis/500
+        tick: dora/timer/millis/50
       outputs:
         - image
+
+  - id: keyboard
+    custom:
+      source: ../operators/keyboard_op.py
+      outputs:
+        - buffer
+        - submitted

operators/webcam.py

@@ -0,0 +1,76 @@
+import os
+import time
+
+import cv2
+import numpy as np
+import pyarrow as pa
+
+from dora import DoraStatus
+
+CAMERA_WIDTH = 960
+CAMERA_HEIGHT = 540
+
+CAMERA_INDEX = int(os.getenv("CAMERA_INDEX", 0))
+CI = os.environ.get("CI")
+
+font = cv2.FONT_HERSHEY_SIMPLEX
+
+
+class Operator:
+    """
+    Sending image from webcam to the dataflow
+    """
+
+    def __init__(self):
+        self.video_capture = cv2.VideoCapture(CAMERA_INDEX)
+        self.start_time = time.time()
+        self.video_capture.set(cv2.CAP_PROP_FRAME_WIDTH, CAMERA_WIDTH)
+        self.video_capture.set(cv2.CAP_PROP_FRAME_HEIGHT, CAMERA_HEIGHT)
+        self.failure_count = 0
+
+    def on_event(
+        self,
+        dora_event: str,
+        send_output,
+    ) -> DoraStatus:
+        event_type = dora_event["type"]
+        if event_type == "INPUT":
+            ret, frame = self.video_capture.read()
+            if ret:
+                frame = cv2.resize(frame, (CAMERA_WIDTH, CAMERA_HEIGHT))
+                self.failure_count = 0
+            ## Push an error image in case the camera is not available.
+            else:
+                if self.failure_count > 10:
+                    frame = np.zeros((CAMERA_HEIGHT, CAMERA_WIDTH, 3), dtype=np.uint8)
+                    cv2.putText(
+                        frame,
+                        "No Webcam was found at index %d" % (CAMERA_INDEX),
+                        (int(30), int(30)),
+                        font,
+                        0.75,
+                        (255, 255, 255),
+                        2,
+                        1,
+                    )
+                else:
+                    self.failure_count += 1
+                    return DoraStatus.CONTINUE
+
+            send_output(
+                "image",
+                pa.array(frame.ravel()),
+                dora_event["metadata"],
+            )
+        elif event_type == "STOP":
+            print("received stop")
+        else:
+            print("received unexpected event:", event_type)
+
+        if time.time() - self.start_time < 20 or CI != "true":
+            return DoraStatus.CONTINUE
+        else:
+            return DoraStatus.STOP
+
+    def __del__(self):
+        self.video_capture.release()

operators/whisper_op copy.py

@@ -0,0 +1,25 @@
+import pyarrow as pa
+import whisper
+
+from dora import DoraStatus
+
+
+model = whisper.load_model("base")
+
+
+class Operator:
+    """
+    Transforming Speech to Text using OpenAI Whisper model
+    """
+
+    def on_event(
+        self,
+        dora_event,
+        send_output,
+    ) -> DoraStatus:
+        if dora_event["type"] == "INPUT":
+            audio = dora_event["value"].to_numpy()
+            audio = whisper.pad_or_trim(audio)
+            result = model.transcribe(audio, language="en")
+            send_output("text", pa.array([result["text"]]), dora_event["metadata"])
+        return DoraStatus.CONTINUE